◼ Research Field
  - In order to lower humanity’s dependency on fossil fuels, biocatalysis can be employed in the production of fine and bulk chemicals. Biocatalysts offer many advantages over traditional chemical synthesis, such as their ability to upcycle waste products like cellulose or carbon dioxide, or the very mild reaction conditions they enable (neutral pH, ambient temperature and pressure). In recent years, the number of biosynthetic pathways has been expanded beyond natural pathways, allowing the synthesis of new-to-nature chemicals via synthetic pathways.

However, the implementation of synthetic pathways into the living cell is challenging due to the delicate balance between growth and product generation. Any energy spent on off-pathway products or futile cycles can impede the implementation of a pathway: key cellular resources like ATP or NADPH may be drained or important metabolite pools such as acetyl-CoA disrupted, rendering the organism incapable of growth. In pathway engineering, a lot of effort is placed on minimizing these interactions, therefore allowing a better allocation of cellular resources. This is referred to as metabolic orthogonality.

Orthogonality can be achieved using non-natural intermediates that the surrounding metabolism does not recognize. However, pathways utilizing these synthetic intermediates still require key cellular resources in the form of cofactors (ATP, NADH, CoA, to name a few). In our group, we aim to expand the concept of orthogonality to those cofactor pools, creating separate cofactors for separate purposes.

◼ Required Research Field of Study
  - For this project, we are looking for a highly motivated student with a background in natural sciences. Previous laboratory experience is a bonus, but not required. The main language in our lab is English, therefore good English proficiency (B2-C1) is important.

◼ Description of Research Activities During the Program
  - This project will focus on generating short orthogonal cascades for the production of chemicals. Mainly, the synthetic enzymes required for efficient catalysis will be developed. Here, you will purify enzymatic candidates, compare their activities, develop high-throughput screens and screen mutant libraries to find improved variants. Towards the end of the project, the variants generated will be characterized biochemically via kinetic assays based on UV-Vis, fluorescence or HPLC-MS analytical methods.

◼ Research Equipment or Software to be Used
  - Instruments for the analysis of enzyme kinetics
  - photospectrometers, plate readers, etc.
  - FPLC for protein purification
  - Softwares associated to the above
  - Software for the analysis of protein structures, potentially computational analysis including molecular docking

◼ Website
  -  https://www.mpi-marburg.mpg.de/1484346/Maren-Nattermann

◼ Research Field
  - Metabolic signaling in obesity and diabetes.

Metabolic disorders, such as obesity and type-2 diabetes, are risk factors for various diseases including cancer and cardiovascular disorders, and the number of obese and diabetic patients is dramatically increasing worldwide.

In the past, we have identified new regulatory mechanisms of adipocyte turnover and adipocyte function through autocrine regulatory loops (Ahmed et al., 2010) and by inflammatory signaling pathways that regulate adipocyte survival and browning (Sassmann et al., 2016). We have also identified positive and negative modulators of glucose-stimulated insulin secretion (Tang et al., 2015; Tunaru et al., 2018) and have analyzed the mechanism mediating obesogenic adipogenesis (Wang et al., 2020a) and adipocyte survival during obesity (Wang et al., 2020b).

More recent work described a new role of the endothelial insulin receptor in insulin action and its inhibition by endothelial adrenomedullin signalling as a central mechanism of obesity-induced diabetes (Cho et al., 2025).

Future work will focus on the regulation of adipocyte and β-cell turnover and function in healthy and disease states as well as on understanding how metabolic disorders such as obesity promote cancer progression and cardiovascular disorders.

◼ Required Research Field of Study
  - molecular biology

◼ Description of Research Activities During the Program
  - lab work, basic research work, working with chemicals, biological reagents, organic tissues, etc. Maybe also microscopy and proteomics.

◼ Research Equipment or Software to be Used
  - Weill be specified and introduced to student(s) after acceptance.

   ※ any specific requirements or important information
      - No allergies to chemicals, biological reagents, organic tissues, and mice.

◼ Website
  -  https://www.mpi-hlr.de/46572/pharmacology

◼ Research Field
  - The main goal of the Department of Digital and Computational Demography is to advance fundamental population science, through the lens of digital and computational perspectives, for the benefit of everyone.

◼ Required Research Field of Study
  - Demography, social sciences, sociology, computer sciences, computational social science

◼ Description of Research Activities During the Program
  - research, data analysis, paper writing and presenting

◼ Research Equipment or Software to be Used
  - laptop, various data, software packages, a programming language for example: R, Python, SQL, Julia, and similar

   ※ any specific requirements or important information
    - Our institute is an interdisciplinary context where scholars from different disciplines collaborate with each other.

◼ Website
  -  https://www.demogr.mpg.de/en

◼ Research Field
  - The Max Planck Computing and Data Facility (MPCDF, formerly known as RZG) is a cross-institutional competence centre of the Max Planck Society to support computational and data sciences. In close collaboration with domain scientists from the Max Planck Institutes the MPCDF is engaged in the development and optimization of algorithms and applications for high performance computing and data analytics as well as in the design and implementation of solutions for data-intensive projects. The MPCDF operates state-of-the-art supercomputers, several mid-range compute systems and data repositories for various Max Planck institutes, and provides an up-to-date infrastructure for data management including long-term archival.

◼ Required Research Field of Study
  - computer science or computational science and engineering

◼ Description of Research Activities During the Program
  - apply data analytics and AI/machine learning methods to HPC performance data

◼ Research Equipment or Software to be Used
  - access to high-performance computers and state-of-the-art software and data infrastructure

◼ Website
  - https://www.mpcdf.mpg.de

【06-A. Dr. Yves Kayser】

◼ Research Field
  - X-ray absorption spectroscopy in fluorescence mode using laboratory-based instrumentation Developments in X-ray sources and detectors have enabled in the past decade to realize an increasing number of instruments for X-ray absorption fine structure (XAFS) measurements on the laboratory scale. Thus, complementary availability to the large-scale infrastructure that synchrotron radiation facilities are is offered. XAFS is an element-selective method where the electronic fine structure of atoms is probed by varying the incident X-ray photon energy around the ionization threshold of an electronic subshell. This technique is sensitive to the oxidation / spin state as well as of the local geometry of the atoms from the probed element. Most of the laboratory-baed instruments realized are, however, designed for transmission mode measurements. This aspect limits the range of samples that can be measured to those that present suitable transmission properties. Samples on a non-transparent substrate, for example electrodes in electrochemistry, or with low concentration, as encountered regularly in catalysis, require therefore a different approach. This project aims at expanding the capabilities of an X-ray spectrometer for XAFS experiments such that measurements can be flexibly realized in transmission or in fluorescence mode and a larger range of samples can be investigated in future. Applicants will have the opportunity to commission the new detection arrangement and provide input to improvements based on data acquired on metallic foils and standardly used chemical complexes. The trainee will gain skills XAFS, including measurement strategies, sample preparation as well as data processing and evaluation. The intern will receive the scientific training necessary to develop and use state-of-the-art instrumentation laboratory-based X-ray spectroscopy instrumentation. This internship might pave the way to future doctoral training.

◼ Required Research Field of Study
  - Chemistry, Physics

◼ Description of Research Activities During the Program
  - In a crystal-based X-ray spectrometer configured in the Joann geometry, an additional measurement mode for X-ray absorption fine structure measurements (XAFS) will be realized by modification of the sample and detector orientation. This measurement mode will allow for acquiring data in fluorescence mode, which is needed for dilute samples or samples on a non-transparent substrate. The development mentioned will require previous beam profiling studies using an X-ray camera and designing a shielding from scattered X-rays as well as an optimization of the sample to detector distance. Following an update of the data processing software, comparative data of both detection modes, fluorescence and transmission type, shall validate the new acquisition mode. Finally, the detection sensitivity shall be assessed as well to assess realistic measurement times for experiments in fluorescence mode.

◼ Research Equipment or Software to be Used
  - laboratory-based high -energy resolution X-ray spectrometer for XAFS and XES

◼ Website
  - https://www.cec.mpg.de/en/research/inorganic-spectroscopy/prof-dr-serena-debeer
  - https://www.cec.mpg.de/en/research/inorganic-spectroscopy/dr-yves-kayser

【06-B. Dr. Kushal Sengupta】

◼ Research Field
  - Mechanistic Studies on Soluble Methane Monooxygenase (sMMO)

sMMO is a complex, multi-component metalloenzyme that catalyzes methane oxidation to methanol via a diiron active site using molecular O2. The DeBeer department has made significant contributions in characterizing sMMO intermediates using cryogenic trapping and techniques such as EPR, Mössbauer spectroscopy, and X-ray methods. In recent years, major efforts have been directed toward studying sMMO under physiological (liquid-phase) conditions. The development of a custom microfluidic setup has enabled real-time spectroscopic studies of sMMO during turnover. These types of experiments, particularly under turnover conditions and at physiologically relevant temperatures, are inherently sample-intensive and require substantial quantities of highly pure and active protein. Over the past two years, we have successfully established all biochemical workflows in-house to produce the sMMO protein components in their active form. This includes optimized expression in native or engineered bacterial hosts, purification under anaerobic conditions, and rigorous activity assays to validate functionality. The predicted reaction mechanism of the catalytic protein involves several intermediates. We plan to further investigate intercomponent interactions, dynamic structural changes, and substrate-specific generation of reactive intermediates.

◼ Required Research Field of Study
  - Students majoring in chemical science, with interests in bioinorganic chemistry and spectroscopy are encouraged.

◼ Description of Research Activities During the Program
  - Mechanistic Studies on Soluble Methane Monooxygenase (sMMO)

sMMO is a complex, multi-component metalloenzyme that catalyzes methane oxidation to methanol via a diiron active site using molecular O2. The DeBeer department has made significant contributions in characterizing sMMO intermediates using cryogenic trapping and techniques such as EPR, Mössbauer spectroscopy, and X-ray methods. In recent years, major efforts have been directed toward studying sMMO under physiological (liquid-phase) conditions. The development of a custom microfluidic setup has enabled real-time spectroscopic studies of sMMO during turnover. These types of experiments, particularly under turnover conditions and at physiologically relevant temperatures, are inherently sample-intensive and require substantial quantities of highly pure and active protein. Over the past two years, we have successfully established all biochemical workflows in-house to produce the sMMO protein components in their active form. This includes optimized expression in native or engineered bacterial hosts, purification under anaerobic conditions, and rigorous activity assays to validate functionality. The predicted reaction mechanism of the catalytic protein involves several intermediates. We plan to further investigate intercomponent interactions, dynamic structural changes, and substrate-specific generation of reactive intermediates.

◼ Research Equipment or Software to be Used
  - FPLC, EPR, UV-Vis, GC, Matlab, Python, etc.

◼ Website
  - https://www.cec.mpg.de/en/home

◼ Research Field
  - Embodied Collective Intelligence: Our research group explores how intelligent collective behaviors emerge through the interaction of sensing, decision-making, and movement—both in animals and in robots. By focusing on how bodies interact with their environments and with others, we study embodied collective intelligence at multiple levels, from individual sensorimotor control to large-scale swarm coordination. Our work combines virtual reality, robotics, AI, and behavioral biology, often in tightly integrated, cross-disciplinary platforms.

Behavioral Evolution: My research group investigates the evolution of animal behaviour using quantitative, comparative approaches in natural environments. Rooted in evolutionary theory, our work addresses long-standing questions—how complex social and cognitive behaviours evolve—through modern computational and experimental methods. We have pioneered the underwater use of computer vision, machine learning, automated behavioural tracking, and 3D environmental reconstruction to generate precise, quantitative measures of behaviour in the field. The project on offer will involve further development of a pipeline that takes underwater video of live animals interacting, tracks their motion and posture, and projects this onto 3D animated models which are then used in underwater playback experiments.

◼ Required Research Field of Study
  (1) Stiffness Optimization of Fins for Fish Schooling: Physics, Mechanical Engineering, Electrical Engineering, Computer Science, Robotics, or Mechatronics

 (2) Multimodal Sensing and Perception for Robotic Fish Schooling: Electrical Engineering, Computer Science, Robotics, Mechanical Engineering, or related fields

 (3) Evolution of Animal Behaviour: Students should have an interest in behavioural biology, computational ethology, or biological animation, with a focus on reconstructing realistic animal movement from empirical data. The project sits at the intersection of animal behaviour research and computer-graphics-based animation, requiring both biological insight and technical curiosity.

◼ Description of Research Activities During the Program
  (1) Stiffness Optimization of Fins for Fish Schooling: Students will investigate how tail and body stiffness influence swimming efficiency in individual robotic fish and in fish schools.

  The work will include:
    - Designing and fabricating robotic fish bodies and fins with different stiffness distributions.
    - Conducting experiments in a laminar flow tank to measure swimming performance (speed, power consumption, efficiency) under controlled flow conditions.
    - Using PIV (particle image velocimetry) to visualize and quantify the surrounding flow fields and wake structures.
    - Analysing data to understand stiffness–fluid–body interactions and identify energy-saving configurations.
    - Contributing to the design of a mechanism that actively tunes body stiffness in real time to optimize propulsion.

   (2) Multimodal Sensing and Perception for Robotic Fish Schooling: Students will develop and integrate multimodal sensing and perception modules for robotic fish to enable robust schooling behavior.

  The work will include:
    - Designing and implementing embedded sensing architectures combining pressure sensor arrays (lateral-line analogues) and cameras.
    - Building and testing sensor modules on robotic fish platforms.
    - Developing signal-processing pipelines to extract meaningful features from pressure and visual data.
    - Implementing and evaluating perception and control algorithms (e.g. machine learning or computer-vision based methods) to detect neighbors and maintain schooling formations.
    - Performing experiments to assess how different sensing configurations affect stability and coordination in robotic fish schools

(3) Evolution of Animal Behaviour: Students will generate 3D animated playbacks of fish behaviour by combining empirical tracking data with model rigging, motion filtering, and animation pipelines in Unity and Blender, ultimately creating lifelike behavioural sequences suitable for underwater display. They will work directly with real behavioural datasets, apply denoising and interpolation methods, and translate observed movement patterns into naturalistic animated avatars for experimental use.

◼ Research Equipment or Software to be Used
  (1) Stiffness Optimization of Fins for Fish Schooling:
    - Laminar flow tank (test bed)
    - Robotic fish prototyping tools (e.g. 3D printer, soft materials, mechanical tools)
    - PIV system for flow field measurement and analysis
    - Electronic measurement tools (oscilloscope, power supply, sensors, DAQ)
    - Relevant software (e.g. MATLAB/Python for data analysis, CFD/CAE tools and CAD for design and simulation)

  (2) Multimodal Sensing and Perception for Robotic Fish Schooling:
    Embedded electronics development platforms (e.g. STM32, Arduino, Raspberry Pi)
    - Robotic fish prototyping tools (3D printing, soft materials, mechanical tools)
    - Circuit design and testing tools (soldering equipment, oscilloscopes, power supplies, sensors)
    - Software for embedded programming, signal processing, and perception (e.g. C/C++, Python, MATLAB, OpenCV, machine-learning frameworks)

(3) Evolution of Animal Behaviour: Students will use Blender for 3D modelling and rigging, Unity for animation, movement logic, and playback control, and Python-based tools for processing keypoint-tracking data, including filtering algorithms, GMM/HMM-derived feature sets, and spline/Bezier interpolation methods. They will also engage with behaviour-tracking frameworks such as Detectron2 and BORIS, which provide the empirical movement data underpinning the animations. 

   ※ any specific requirements or important information

    (1) Stiffness Optimization of Fins for Fish Schooling
      Background in signal processing and/or modelling (e.g. hydrodynamics, mechanism modelling)
      - Experience with numerical simulation (e.g. CFD, multibody or body dynamics) is highly desirable
      - Mechanical design skills (CAD, CAE)
      - Strong hands-on skills and interest in prototyping and experiments
      - Motivation to work in an interdisciplinary environment (physics, engineering, and robotics) 

   (2) Multimodal Sensing and Perception for Robotic Fish Schooling:
    - Experience with embedded systems (e.g. STM32, Arduino, Raspberry Pi) and basic circuit design
    - Knowledge of sensor signal processing and/or machine learning
    - Familiarity with computer vision techniques is a plus
    - Hands-on skills in prototyping (electronics and mechanical integration)
    - Interest in bio-inspired robotics and working in an interdisciplinary team

◼ Website
  - www.ab.mpg.de

◼ Research Field
  - Circadian biology is the study of the internal 24-hour timing system that regulates physiology, behavior, and metabolism. Nearly every cell in the body contains a molecular clock, and these clocks are coordinated by a central pacemaker in the brain. Understanding how the circadian system aligns, or fails to align, with the external environment is essential for research areas ranging from sleep science and cognitive performance to metabolic and mental health.

A central challenge in circadian research is accurately determining an individual’s internal biological time. One of the most widely used markers is the dim light melatonin onset (DLMO), the point in the evening when melatonin levels begin to rise. Because melatonin secretion reflects output from the central circadian pacemaker, DLMO provides a robust measure of circadian phase. Precise estimation of DLMO is critical for diagnosing circadian rhythm disorders, timing light-based interventions, and interpreting inter-individual differences in sleep timing.

Modern circadian research increasingly relies on quantitative methods to extract meaningful information from physiological data. As datasets become larger and more complex, often involving wearable sensors, repeated measurements, and substantial individual variability, researchers require analytical tools that can handle nonlinear dynamics, uneven sampling, and biological noise. This shift has driven growing interest in flexible, data-driven modelling frameworks capable of providing robust and interpretable estimates of key circadian markers. 

The research field draws on ideas from chronobiology, data science, and applied statistics, blending biological understanding of circadian regulation with computational techniques capable of extracting meaningful temporal markers from real-world physiological signals. Students entering this area develop widely transferable skills, including time-series modelling, uncertainty quantification, statistical inference, and the ability to work with high-resolution biological datasets.

◼ Required Research Field of Study
  - Mathematics, Electrical Engineering, Biomedical Engineering, Computer Science

◼ Description of Research Activities During the Program
  - Internship: Developing a GAMM-based method for estimating dim light melatonin onset (DLMO)

 (Project Overview)
This internship focuses on advancing a new method for determining the dim light melatonin onset (DLMO), a key physiological marker used to assess the human circadian clock phase. Accurate and reproducible DLMO estimation is central for circadian research, clinical applications, and understanding individual differences in sleep timing. You will gain hands-on experience with modeling, signal analysis, and biological datasets.

 (Background and Motivation)
Current DLMO estimation methods often rely on subjective thresholds or algorithms that can be sensitive to model assumptions. A promising alternative is to use generalized additive mixed models (GAMMs), which provide a flexible, data-driven way to model melatonin levels as smooth curves. GAMMs avoid arbitrary thresholds and rigid breakpoints, can capture individual differences, handle irregular sampling, and use the curve’s derivative to identify the point of steepest rise. This offers a more robust estimate of DLMO along with interpretable uncertainty. 

This internship contributes directly to the ongoing development of the open source dlmoR package, which aims to provide a modular suite of DLMO estimation methods that users can compare within a common analytical framework.

 (What You Will Do)
• Develop and implement a GAMM-based approach for estimating DLMO.
• Compare GAMM-derived estimates to existing methods (e.g., hockey-stick, thresholding).
• Contribute code, documentation, and reproducible workflows to the dlmoR package.
• Opportunity to collect and process a time-dense salivary melatonin dataset to serve as ground truth for model validation. 

 (Required Skills)
• Strong programming skills in R, Python, or MATLAB.
• Ability to work with data, implement models, and write clear, maintainable code. 

 (Preferred Skills)
• Experience in signal processing, mathematical modeling, or statistical methods.
• Familiarity with GAM/GAMM frameworks (e.g., mgcv), nonlinear modeling, or time-series analysis.

◼ Research Equipment or Software to be Used
  - Hardware: Computer, Software: R, Python

◼ Website
  - https://www.tscnlab.org

◼ Research Field
  - synaptic physiology

◼ Required Research Field of Study
  - electrophysiology, molecular biology

◼ Description of Research Activities During the Program
  - Our laboratory seeks to elucidate the regulatory mechanisms underlying synaptic transmission and its plasticity, with a particular emphasis on synaptic vesicle dynamics and dendritic spine architecture. We integrate patch-clamp electrophysiology with advanced molecular biological approaches to achieve this goal

◼ Research Equipment or Software to be Used
  - Patch clamp set up (HEKA or Axon), axograph, Imaris, confocal microscope

◼ Website
  - https://www.mpinat.mpg.de/contact-citycampus

◼ Research Field
  - The project will be performed within the field of micromechanics and hydrogen embrittlement. The research is focused on understanding how hydrogen interacts with materials at the micro- and nano-scale and how these interactions lead to mechanical degradation and failure. It combines micromechanical testing, like nanoindentation and nanoscratching, and materials science to study hydrogen transport, trapping, and its effects on dislocation behavior, crack initiation, and fracture processes. The goal is to predict and mitigate hydrogen-induced damage in structural materials used in energy, transportation, and industrial applications.

◼ Required Research Field of Study
  - Materials Science

◼ Description of Research Activities During the Program
  - Barrier coatings are crucial for protecting structural materials in hydrogen-rich or high-temperature environments, where accelerated embrittlement, oxidation, and degradation severely limits materials lifetimes. MAX-phase barrier coatings such as Cr₂AlC could offer strong protection in hydrogen-rich and high-temperature environments due to their thermal stability and oxidation resistance from protective alumina scales. However, experimental understanding of hydrogen–coating interactions, particularly under in-situ charging, remains limited, motivating further study.

This project aims to study and evaluate the mechanical stability of Cr₂AlC coatings under controlled electrochemical charging, building on our previous findings in Ti-based MAX phases. This will be performed by nanoindentation and nanoscratch testing of electrochemically charged samples with hydrogen. The analysis will be supported by microstructural characterization by scanning electron microscopy (SEM) and analyses related to hydrogen absorption and transport. The goal is to establish structure–property relationships by correlating microstructural changes, hydrogen uptake, and mechanical performance. Ultimately, this work will provide experimental evidence for the viability of Cr₂AlC as a hydrogen-resistant barrier coating.

This project offers hands-on experience with advanced characterization techniques and a direct introduction to novel research on hydrogen-resistant materials. The student will gain practical skills in nanoindentation, SEM analysis, and electrochemical methods, while also learning how to interpret complementary data from various additional techniques. The student will gain experience in academic collaborations in an international research environment.

◼ Research Equipment or Software to be Used
  - Techniques directly used by the student:
    • Nanoindentation: Mechanical properties of the as-deposited Cr2AlC and under in-situ hydrogen charging.
    • Scanning Electron Microscopy (SEM): Looking into both the surface and cross section of the samples, studying the microstructural changes after mechanical testing and hydrogen exposure.
    • Electrochemical testing: various techniques will be used (CV, CP and CA) for controlled hydrogen charging, while monitoring the charging kinetics and stability.

 Additional supporting techniques (not used directly by the student):
    • XPS - X-ray photoelectron spectroscopy
    • XRD - X-ray diffraction
    • TDS -Thermal desorption spectroscopy

◼ Website
  - https://www.mpie.de

◼ Research Field
  - “Advancement of a Microscale Model for Electrosynthesis using OpenFOAM”

Target: The goal of the internship is to enhance and refine a microscale electrosynthesis model in OpenFOAM. The fundamental modeling framework is already in place, providing a solid basis for further development.
The next steps focus on extending the model to implement complex electrochemical reaction mechanisms, enabling more realistic descriptions of electrosynthesis pathways. Additionally, complex electrode microstructures will be simulated on a high-performance computing environment to capture local transport and reaction gradients. Finally, parameter studies will be performed to identify optimal operating conditions and support the design and improvement of experimental setups.

Motivation and Background: Modeling electrosynthesis is driven by the growing need for more sustainable chemical production pathways. Electrosynthesis offers a promising alternative to fossil-based processes by using electricity - ideally from renewable sources - as a clean reagent for chemical reactions. By simulating the underlying physicochemical phenomena at the microscale, researchers can better understand reaction selectivity, optimize catalyst behavior, and design more efficient electrode architectures. Such modeling efforts accelerate the development of scalable, low-waste, and energy-efficient processes, ultimately supporting the transformation toward a greener chemical industry and a more sustainable production landscape.

 (Task)
  1. Familiarization and immersion with the mathematical modeling approach, fundamentals of electrosynthesis and the existing OpenFOAM solver.
  2. Solver development, setup of simulation cases, meshing complex structures and performing parameter variation studies

 (Requirements)
  o Studies in the fields of engineering, physics, chemistry, computer science, or comparable.
  o Fundamental knowledge of OpenFOAM and basic programming skills (C++) are required.
  o Interest in electrochemical processes, energy systems, and their mathematical modeling.
  o Strong communication and writing skills in English.
  o Independent working style and ability to collaborate effectively in a team.

This internship provides an excellent opportunity to engage in meaningful research on clean energy technologies and develop valuable skills in modeling and implementation of complex physical phenomena, data analysis, and applied research.

◼ Required Research Field of Study
  - engineering, physics, chemistry, computer science, or comparable

◼ Description of Research Activities During the Program
  1. Familiarization and immersion with the mathematical modeling approach, fundamentals of electrosynthesis and the existing OpenFOAM solver.
  2. Solver development, setup of simulation cases, meshing complex structures and performing parameter variation studies

◼ Research Equipment or Software to be Used
  - Simulation Software like OpenFOAM and COMSOL Multiphysics

  ※ any specific requirements or important information

  Requirements:
  o Studies in the fields of engineering, physics, chemistry, computer science, or comparable.
  o Fundamental knowledge of OpenFOAM and basic programming skills (C++) are required.
  o Interest in electrochemical processes, energy systems, and their mathematical modeling.
  o Strong communication and writing skills in English.
  o Independent working style and ability to collaborate effectively in a team.

◼ Website
  - https://www.ict.fraunhofer.de/en.html

◼ Research Field
  - Physical engineering / microfluidics / CAD design / Simulation
    Point-of-care test systems
    Organ-on-a-Chip (Joint, Liver, Lung, Brain-on-a-Chip)
    Bioprint (single cell performance center)

◼ Required Research Field of Study
  - Physics, Microfluidics, Engineering or Natural sciences

◼ Description of Research Activities During the Program
  - The planned topic is microfluidics and Organ-on-a-Chip technologies, focusing on the design, simulation, and validation of microfluidic chips for biological applications.

◼ Research Equipment or Software to be Used
  - SolidWorks, Comsol or ANSYS, Oxygen Plasma, Incubator, Soft Lithography

  ※ any specific requirements or important information

     - Fluent in spoken and written English

◼ Website
  - https://www.imm.fraunhofer.de/

【13-A. Dr. N.Jon Shah】

◼ Research Field
  - Topic: Advanced MRI research: from system hardware to quantitative brain imaging

Magnetic Resonance Imaging (MRI) is one of the most powerful neuroscientific and diagnostic tools to access the in vivo human brain non-invasively. At ultra-high magnetic fields (such as 7 Tesla), MRI further offers exceptional levels of detail – but also brings exciting scientific and multi-disciplinary challenges including hardware design, data acquisition and image reconstruction.

Under my leadership, the institute of neuroscience and medicine – 4 (INM-4), Forschungszentrum Jülich primarily focuses on the development, experimental validation and the clinical and preclinical implementation of novel and multimodal neuroscience methods. We have established a globally unique platform for translational neurological research based on combined ultra-high field MRI and PET. Furthermore, the institute’s activities are embedded in national and international networks and collaborations. Therefore, the selected students can experience how cutting-edge MRI research works across multiple levels, ranging from building the technology itself to developing advanced data-analysis pipeline. They may focus on one or more research areas that match their background and interests while being exposed to the broader landscape of MRI science. A few of potential topics are below.

  • Next-generation MRI hardware development: Students can learn how MRI hardware is designed, simulated and tested. This includes working with radio-frequency coil designs, understanding how hardware influences image quality and gaining hands-on experience with coil testing or measurement steps. This offers a rare opportunity to see the engineering side of MRI and how hardware innovations can be combined with cutting-edge software innovation leading to new imaging capabilities. This training offers a rare opportunity for the students.

  • Advanced MR data acquisition, reconstruction, and analysis: Students will also be introduced to how MRI signals are acquired and converted into images. They can learn about signal processing, image reconstruction and quantitative brain mapping, and both classical and data-driven analysis methods using AI and deep learning. AI-aided reconstruction is rapidly gaining acceptance in community and is thus right at the forefront of MRI research; students trained in AI reconstruction are highly sought after by academia and industry.

  • Structural, metabolic, molecular and functional brain imaging, and spectroscopy: my institute also conducts research on how MRI and MR spectroscopy can be used to study brain structure, physiology, metabolism and function. Students will be exposed to a variety of imaging contrasts and scientific questions, and will have opportunities to attend seminars and group meetings covering diverse MRI applications.

Overall, students participating in this internship will be able to closely engage with our activities under supervision by myself and our expert in the topic.

◼ Required Research Field of Study
  - MRI is a multi-disciplinary field, and we look for highly motivated students from medicine, physics, chemistry, biology, engineering or computer science.

◼ Description of Research Activities During the Program
  - During the 6-month internship, the student will be involved in hands-on MRI research that can span hardware and data acquisition, reconstruction, or quantitative imaging, depending on the student’s background and interests. Exposure to AI / machine learning will comprise a significant part of these projects. The projects will be designed to provide both foundational training and a focused research component, with flexibility to adapt as the student progresses.

  - Month 1 (Sep. 2026) - Orientation, Setup, and Foundations
The student will begin by settling into the research environment, setting up the required software tools and learning core concepts in MRI.
This includes introductory reading, basic tutorials, and first simple exercises such as loading datasets, visualising signals and performing basic Fourier-based image reconstruction.

     - Months 2-3 (Oct.-Nov.) – Exposure to Different Research Components
  In the following months, the student will be introduced to a range of possible research directions pursued in the group:
  1. Hardware & RF coil development
  2. Image reconstruction and quantitative mapping
  3. Data processing, signal analysis and interpretation 

  - Months 4-5 (Dec.-Jan.) – Focused Project Work
After gaining an overview of the research topics, the student will focus on one selected project direction.

  - Months 6 (Feb.) – Final Analysis, Documentation & Presentation
In the final month, the student will summarise findings in a short technical report, document code and analysis steps, and prepare and deliver a final presentation to the team.

   - Mentoring environments

The student will be integrated into an active and supportive research environment. In addition to regular one-to-one guidance from supervisors, the student will benefit from multiple learning opportunities within the institute:
  • Weekly group meetings, where ongoing research projects are presented and discussed.
  • Monthly team meetings, which bring together researchers working on specific MRI methods. This provides an opportunity to learn from ongoing projects, ask questions and receive feedback from senior scientists.
  • Monthly student meeting, where students from different groups (e.g. PET, Digital Translational Neuroimaging) in INM-4 present and exchange ideas. This broader interaction allows the student to gain exposure to different imaging modalities and improve communication skills.
  • Monthly Korean Researchers’ Seminar Series where Korean scientists working at FZJ give seminars about their research and build a sense of community. This fosters a supportive cultural community and gives the student additional opportunities to learn other things beyond their project. We also have several colleagues from South Korea who will also participate in events with the students.
  • Open door environment – students are encouraged to interact with postdocs and PhD researchers, seek feedback and ask for help when needed.

◼ Research Equipment or Software to be Used
  - Equipment & Data Access:
  Two 3 T clinical scanners (one with BrainPET insert)
  One 7 T clinical scanner (with a unique BrainPET insert)
  One 7 T animal scanner

  - Computing Resources
  No GPU or HPC infrastructure may not be required for the student’s project, but optional access to lab computing clusters and to the Europe’s fastest supercomputer (JUPITER) can be arranged if the student explores more advanced reconstruction or AI-based extensions. 

  - Software & Programming Tools
  Python or MATLAB
  Other MRI related toolboxes and software

◼ Website
  - https://www.fz-juelich.de/de/inm/inm-4

【13-B. Dr. Seong Dae Yun】

◼ Research Field
  - Brief introduction:

This project aims to apply state-of-the-art deep learning techniques to ultra-high resolution functional magnetic resonance imaging (fMRI), under the scientific leadership of Dr. Seong Dae Yun, Team Leader of the Sequences and Scientific Computing Team at INM-4, Forschungszentrum Juelich (FZJ). MRI provides a unique, non-invasive window into the living human brain and represents one of the most powerful modalities for probing neural function in vivo.

The integration of deep learning-based image reconstruction with ultra-high-resolution fMRI is still in its early stages, yet it holds substantial innovative potential for the neuroscience community. By overcoming fundamental limitations of conventional fMRI techniques, the proposed approach enables the investigation of brain function at the mesoscale level, offering deeper insights into the brain’s intrinsic computational architecture.

Beyond basic neuroscience, the developed methods are highly relevant for clinical research, enabling improved characterization of functional alterations in neurological conditions such as brain tumors and affective disorders. Overall, the project provides an interdisciplinary research environment at the interface of neuroscience, medical imaging, and artificial intelligence, offering excellent training opportunities for students interested in cutting-edge brain imaging and computational methods.

Students joining this project will gain hands-on experience in MRI physics, advanced data acquisition, and modern AI-based reconstruction techniques applied to real neuroimaging data, with opportunities to contribute to research abstracts and publications in leading international conferences and SCI journals.

Keywords: Neuroscience, Brain Function, MRI, fMRI, Ultra-High Resolution Imaging, Data Acquisition and Reconstruction, Deep Learning, Artificial Intelligence, Image Analysis, Clinical Neuroimaging, Neurological Disorders, Neurodegenerative Diseases

◼ Required Research Field of Study
  - Applicants with background or interest in the following fields are encouraged to apply. Prior expertise in MRI or related technical domains is not required. Familiarity with a subset of the areas below is desirable but not mandatory, and motivated students from diverse academic backgrounds are welcome. The Principal Investigator, Dr. Seong Dae Yun, will provide comprehensive scientific guidance and hands-on training throughout the research period.

◼ Description of Research Activities During the Program
   1. Research Purpose:
The human neocortex, a ~3–5 mm thick sheet forming the outer layers of the brain, underlies our highest cognitive and perceptual functions. Its structure is organized into distinct cortical layers, each characterized by specific neuronal populations, connectivity patterns, and computational roles. Non-invasive investigation of human brain function at such layer-specific spatial scales can be achieved using functional magnetic resonance imaging (fMRI). As the laminar-level investigation provides critical insights into the fundamental computational units of the brain, an increasing number of fMRI studies have focused on this direction.

Despite substantial progress, reliable detection of layer-specific neural activity remains challenging. While submillimeter-resolution fMRI techniques have been developed to probe cortical layers, the inherently low signal-to-noise ratio (SNR) at this spatial scale often hampers robust and reproducible characterization. In addition, standard echo-planar imaging (EPI) techniques commonly used in fMRI impose limitations on the accurate spatial correspondence between functional signals and anatomical references.

This project aims to address these challenges by applying state-of-the-art deep learning techniques (Yun et al., 2025) to a novel ultra-high-resolution fMRI framework based on TR-external EPIK (Yun et al., 2022), under the scientific leadership of Dr. Seong Dae Yun. Specifically, the deep learning framework is designed to reconstruct fMRI images with enhanced signal-to-noise ratio (SNR) and improved structural fidelity, while further increasing effective spatial resolution through super-resolution strategies.

As the application of deep learning to layer-specific fMRI remains at a frontier stage, this project represents a cutting-edge methodological advancement beyond current state-of-the-art techniques. By enabling more reliable and accurate laminar-level functional mapping, the proposed framework establishes a strong foundation for translational applications, including clinically relevant studies in patient populations such as individuals with brain tumors, where precise functional characterization is of critical importance. 

  2. Research Tasks
    2.1. Initial Training & Research Environment Setup (Month 1)
      - Dr. Seong Dae Yun will provide introductory lectures covering the fundamental principles of MRI and functional MRI (fMRI).
      - The student will set up the research environment required for the project, including obtaining MRI system access (Level 1), configuring access to high-performance supercomputing resources, and installing software packages for data processing and analysis (e.g., SPM, FSL, and ANTs).
      - In parallel, the student will conduct guided literature reading to build a solid foundational understanding of MRI and fMRI methodologies relevant to ultra-high-resolution imaging.

                 2.2. Ultra-High Resolution fMRI Sequence (Months 2 - 3)
      - An ultra-high-resolution fMRI sequence based on TR-external EPIK will be implemented on a 7T MRI scanner, targeting whole-brain coverage with 0.4–0.5 mm spatial resolution to enable the investigation of layer-specific neural activity. Multiple imaging protocols will be systematically evaluated to determine optimal acquisition parameters.

     - The student will complete the required MR scanner operation courses for scanning healthy human participants (Level 2 / Level 3), becoming qualified to operate the MR scanner independently under institutional guidelines.
    - Based on intermediate methodological results, research abstracts will be prepared and submitted to relevant international conferences.

   2.3. AI-driven Deep Learning fMRI Reconstruction (Months 4 - 6)
    - A deep learning-based reconstruction framework will be developed to address the intrinsically low signal-to-noise ratio (SNR) and image artefacts associated with layer-specific fMRI.
    - In addition, a super-resolution reconstruction strategy will be implemented to further enhance effective spatial resolution by approximately 15–20%, thereby improving the accuracy of laminar-level response characterization.
    - These methods will be developed and trained using supercomputing resources.
    - The performance of the proposed approaches will be quantitatively evaluated against conventional reconstruction techniques using established image quality and functional metrics.

   2.4. Data Acquisition, Analysis and Scientific Writing (Months 5 - 6)
    - In parallel with sequence development and reconstruction work, fMRI data will be acquired from healthy human participants using a 7T MRI scanner.
    - The student will learn advanced fMRI data processing and analysis workflows to accurately map functional activity onto high-resolution anatomical images.
    - The developed methods will subsequently be applied to fMRI datasets from patients with brain tumors, enabling more precise characterization of functional alterations in tumor-affected brain regions.

 3. Expected Outcomes
  3.1. “Hands-on experience with cutting-edge fMRI technology”:
  The student will acquire hands-on experience in operating 7T MRI systems, performing ultra-high-resolution fMRI experiments, and gaining an in-depth understanding of the mechanisms underlying human brain function.

  3.2. “Expertise in AI-based image reconstruction and high-performance computing”:
  Through the development and evaluation of deep learning-based reconstruction models on high-performance supercomputing platforms, the student will acquire strong computational and analytical skills directly applicable to careers in artificial intelligence, imaging science, and biomedical engineering.

  3.3. “Opportunities to contribute to international conferences and publications”:
  The student will actively participate in the preparation of conference abstracts and manuscripts for submission to leading international conferences and high-impact peer-reviewed journals, thereby building a competitive early-stage research portfolio.

  3.4. “Strong foundation for future academic researcher”:
  The student will develop technical proficiency, research independence, and collaborative skills, providing solid preparation and motivation for future academic training at the Master’s and PhD levels.

◼ Research Equipment or Software to be Used
  - This project will make use of the following research equipment and software environments.

   1) Research Equipment: 3T/7T MRI Scanners with fMRI Stimulation Systems
    Our group operates a state-of-the-art 7T Siemens Magnetom Terra scanner as well as a widely used clinical-standard 3T Siemens Prisma system. These MRI platforms are optimized for advanced structural, functional, and physiological imaging of the human brain. Both systems will be utilized in this project to acquire high-quality, ultra-high-resolution neuroimaging data for methodological development and validation.

   2) High-Performance Computing (HPC) Resources
    Dr. Seong Dae Yun has dedicated access to high-performance supercomputing resources at FZJ for advanced MR image reconstruction and deep learning research. These resources enable the training of high-capacity neural networks on large-scale neuroimaging datasets—computational tasks that are not feasible on standard workstations—and substantially accelerate algorithm development, testing, and optimization.

  3) Image Reconstruction & Scientific Computing: MATLAB, Python, C/C++
    This project will employ MATLAB, Python (including deep learning frameworks such as PyTorch and TensorFlow), and C/C++ for algorithm development, numerical simulation, and data analysis. Prior experience with these environments is advantageous but not mandatory. Familiarity with Linux-based systems is recommended to ensure an efficient workflow and effective use of HPC resources.

      4) Functional MRI Data Processing Tools: SPM, FSL, ANTs
  Functional MRI data acquired in this project will be processed using widely adopted neuroimaging toolkits such as SPM, FSL, and ANTs. These platforms provide essential tools for fMRI preprocessing, statistical modeling, and high-accuracy anatomical registration, forming the backbone of reliable and reproducible functional neuroimaging analysis.

   ※ any specific requirements or important information

      - Students will actively contribute to ongoing scientific research while gaining practical skills in functional MRI and deep learning techniques. As the project is research-driven, students with genuine interest, curiosity, and a strong motivation to learn will benefit most from the experience. Based on achievements, students will have opportunities to write research abstracts and papers for submission to leading international MRI conferences and high-impact journals.

◼ Website
  - https://www.fz-juelich.de/en/inm/inm-4

【13-C. Dr. Kyesam Jung】

◼ Research Field
  - This program is in the field of computational neuroscience including cognitive neuroscience, psychology, clinical neuroscience, network neuroscience and multimodal neuroimaging. We focus on relationships between brain and behavior using cognitive and clinical neuroimaging data.

◼ Required Research Field of Study
  - Neuroscience, Psychology, Computational Neuroscience, Network Neuroscience, Cognitive Neuroscience

◼ Description of Research Activities During the Program
  - Overview
  This 6-month internship offers undergraduate students an opportunity to participate in clinical or cognitive neuroscience projects that combine experimental task design, multimodal neuroimaging, network analysis, and machine learning. You will work with multimodal MRI data to explore relationships between human brain and behavior.

   You will gain hands-on experience with:

    - Cognitive task paradigms related to attention and cognitive control
    - Processing multimodal MRI data (e.g., structural and functional neuroimaging)
    - Brain connectome construction and analysis
    - Basic meta-analytic and statistical methods used in human brain MRI
    - Applying machine learning to neuroimaging data

     Training Environment and Supervision
The goal of the internship is for you to experience the full research cycle—from formulating questions to interpreting data and writing up results—and to contribute to the main parts of a research paper. The project will be conducted under the supervision of the principal investigator (Kyesam Jung) and the group leaders in INM-7 who will provide regular feedback and mentoring.

◼ Research Equipment or Software to be Used
  - FreeSurfer, FSL, SPM, Python, MATLAB

    ※ any specific requirements or important information
      - The project is suitable for highly motivated students with an interest in cognitive neuroscience, clinical neuroscience, psychology, or computational neuroscience. Prior experience with MRI or advanced programming is helpful but not mandatory; guidance and training will be provided through the program.

◼ Website
  - https://www.fz-juelich.de/en/inm/inm-7

【14-A. Dr. Sampuma Chakrabati】

◼ Research Field
  - Pathogens interact with our nerves directly and indirectly during infection, causing nervous system dysfunction. Many viruses, including varicella zoster and herpes simplex, remain latent in sensory neurons throughout our lives, sporadically resurfacing to cause pain and itch. Sampurna Chakrabarti and her team seek to understand the host–pathogen interactive mechanisms leading to pain by combining functional and proteomic signatures at the single-neuron level. More details can be found in the website: https://www.helmholtz-hzi.de/en/research/research-groups/details/pathways-in-infection-and-nociception/

◼ Required Research Field of Study
  - Neuroscience, Biology, Electrophysiology

◼ Description of Research Activities During the Program
  - Immunohistochemistry/in-situ hybridization of sensory neurons from mouse and nor humans, cell culture, bioinformatics analysis of RNA-seq or proteomics data

◼ Research Equipment or Software to be Used
  - Some interest in programming with R and python would be useful. Students would be trained on immunohistochemistry and microscopy.

◼ Website
  - https://www.helmholtz-hzi.de/en/

【14-B. Dr. Michael Kolbe】

◼ Research Field
  1. Host/pathogen interactions
  2. Structure & function of macromolecules involved in bacterial pathogenesis
  3. Bacterial effector protein secretion mechanisms
  4. Molecular Mechanisms of innate immunity
  5. Biophysical hybrid approaches

Manipulation of human host cells is a fundamental challenge for all pathogens. To understand host-pathogen interaction and pathogenesis, we examine the characteristics, functionalities and interactions of molecular structures involved in the survival and multiplication of bacteria within the host.
One example of such nanomachine is the type III secretion system (T3SS), a membrane-embedded nanosyringe-like complex that allows the direct delivery of proteins, known as effectors, into the cytosol of human cells. The T3SS is a highly conserved virulence machinery of Gram-negative bacteria, and thus it represents an attractive target for novel anti-infectives. The structural core of the T3SS is a ~3.5 multi-megadalton complex assembled from more than fifteen different proteins that spans the two lipid bilayers of Gram-negative bacteria. The current challenge we face is to understand how structural switches in this bacterial secretion apparatus allow the recognition and secretion of effectors in a hierarchical manner and what kind of protein-protein interactions can drive bacterial invasion. We integrate high-end technologies like X-ray lasers and electron cryo-microscopes with other biophysical methodologies to study the functional dependence of structural determinants in T3SSs from water-borne bacterial pathogens and investigate the rules for effector protein secretion, transport dynamics and regulation of the T3SS.

In addition, we have a strong interest in uncovering the strategies used by Gram-negative organisms to subvert the antibacterial response of human cells. Components of the tip of the T3SS apparatus interact with host membranes to allow the translocation of effectors directly to the human cell cytosol. How the translocon components assemble and insert into host membranes to form pores are under investigation. We also focus on the molecular interactions of T3SS effector proteins with host components and their signaling cascade that drives cellular subversion. Shigella, the causative agent of diarrhoea and other gut-associated diseases, invades the human colonic epithelium and avoids clearance by promoting cell death of resident immune cells in the gut. Different modalities of cell death (pyroptosis, necroptosis and cell death programs involving alternative caspases) have been linked to the killing mechanism. Although these modalities may not be mutually exclusive and may progress simultaneously, we evaluate the contribution of each program in dying cells with special focus on the T3SS dependency.

Pseudomonas aeruginosa is an adaptive environmental bacterium and an important opportunistic pathogen, which causes devastating acute as well as chronic, persistent infections. Due to its high ability of adaptation to different adverse environmental settings and multidrug resistance, this opportunistic pathogen poses a particular threat in public health and thus the urgency of developing new antibiotics is critical. To bypass drug resistance, we are interested in finding novel molecular mechanisms underlying virulence in P. aeruginosa. For this, we combine multiple omics data of clinical isolates with microbiological, biophysical and structural biology methodologies to elucidate structure-function relationships of novel proteins associated with virulence in P. aeruginosa.

We integrate interdisciplinary approaches to advance our understanding of the assembly and three dimensional structure of key bacterial components involved in virulence pathways and their interaction with the host responses to allow us the design of molecular drugs for the treatment of Gram-negative bacterial infections.

◼ Required Research Field of Study
  - biochemistry, bioinformatics, physics

◼ Description of Research Activities During the Program
  - research work and lab duties

◼ Research Equipment or Software to be Used
  - office software; origin, gimp or ImageJ

  ※ any specific requirements or important information
    - motivation, English is mandatory, students will participate in group seminar and journal club;

◼ Website
  - https://www.cssb-hamburg.de/research/michael_kolbe/index_eng.html

【14-C. 참여 포기 (26.03.03)】

【14-D. Dr. Jan Schlegel】

◼ Research Field
  - Our research focuses on deciphering and influencing the biological codes of pathogens at the molecular level. When we think of a pathogen, for example a single virus particle, we usually have a simplified picture in mind of what it looks like and how it is structured. However, we neglect how differently this individual particle - even with identical genetic equipment - can be structured. As these different forms of appearance influence the properties of the pathogen, it is important to understand them better in order to contain infectious diseases. The diversity of these manifestations is due to the interaction of different biological codes. Our team has set itself the task of developing new technologies to decipher these codes in order to investigate their physiological relevance and to be able to influence them. Research into these molecular codes is hampered in particular by two hurdles:
  1) the nanoscopic size of many pathogens
  2) the complexity of life cycles and interactions with their environment

The first hurdle is often solved by signal amplification through the simultaneous measurement of many pathogens (“bulk”), which, however, results in the loss of information about heterogeneity. By using high-throughput technologies with single particle resolution and advanced microscopy methods, we can detect and analyze this diversity.

To better understand the complex interactions of pathogens with their environment, we use synthetic biology methods that allow us to investigate certain questions in a defined and simplified system. For example, we can build a highly simplified artificial cell to analyze the binding behavior of viruses. By using environment-sensitive reporter molecules, we also investigate the collective biophysical properties of pathogens.

◼ Required Research Field of Study
  - Biophysics, Advanced Microscopy, Virology, Synthetic Biology

◼ Description of Research Activities During the Program
  - Cell culture, Virus particle purification, microscopy

◼ Research Equipment or Software to be Used
  - Clean bench, pipettes, centrifuges, microscopes, Fiji

◼ Website
  - https://www.helmholtz-hzi.de/code

【14-E. Dr. Andriy Goychuk】

◼ Research Field
  - We develop theoretical and computational models to improve the understanding of inflammatory responses to infection on the cell and tissue level, as well as the organization of the genome and protein assemblies in the cell nucleus. This organization is often perturbed in disease states, such as during viral infection.

The methods that we use are tailored to the research question at hand and include deterministic and stochastic models ranging from spatially resolved field theories to agent-based and well-mixed descriptions. We validate these theories in close collaboration with experiment, which also helps us to refine the model assumptions, and which sometimes provides inspiration.

◼ Required Research Field of Study
  - (Theoretical) Physics | Mathematics | Mathematical or Theoretical Biology | (Theoretical) Chemistry | Chemical Engineering

◼ Description of Research Activities During the Program
  - The students will pursue one of the following projects in close collaboration with me and PhD students in my group:
  1. Simulate how transcription factors bind to and deform DNA
  2. Study hydrodynamic interactions between immune cells using Finite-Element methods
  3. Study how viral reproduction and gene expression reorganizes the genome
  4. Implement vertex models of tissue dynamics

◼ Research Equipment or Software to be Used
  - Laptops, High-Performance Computing facilities, Python, Julia, Mathematica, C/C++

◼ Website
  - https://www.helmholtz-hzi.de/en/research/research-groups/details/mechanochemistry-of-inflammation/

【15-A. Dr. Christine Beemelmanns】

◼ Research Field
  - The group of Prof. Christine Beemelmanns focuses on the identification and functional analysis of novel anti-infective natural products from microbial communities. Co-cultivation studies as well as cell-based assays in combination with chemical-analytical and molecular-biological methods are used to evaluate and prioritize novel natural product producers. The group uses established and innovative metabolomic-, activity and genome-based methods to identify and determine the structure and biosynthesis of the secreted natural products. Based on the isolated novel natural substances, the functional analysis and evaluation of their range of effects is carried out.

◼ Required Research Field of Study
  - natural product chemistry

◼ Description of Research Activities During the Program
  - natural product chemistry

◼ Research Equipment or Software to be Used
  - HPLC Purification, NMR analysis, fermentation of bacteria or fungi, mass spectrometry methods

  ※ any specific requirements or important information
    - should be able to either perform bacterial fermentation or perform natural product chemistry based purification and structural analysis

◼ Website
  - https://www.helmholtz-hips.de/de/forschung/people/person/prof-dr-christine-beemelmanns/

【15-B. Dr. Tobias A.M.Gulder】

◼ Research Field
  The goal of our group is to explore the world of microbial natural products for the targeted discovery and optimization of compounds to fight infectious diseases. Using modern bioinformatic approaches and the development and application of molecular biology and biotechnology tools, we contribute to the discovery of novel bioactive substances from microbial sources. By altering the genetic pathways involved in natural product biosynthesis, we enable targeted structural optimization and improved production of these substances. We examine in detail the enzymatic processes Nature uses to build complex natural products, making particularly interesting enzymes usable in the lab, and applying them for efficient biocatalytic or chemo-enzymatic drug synthesis. Overall, our research not only enables efficient exploration of natural products, but also facilitates the systematic investigation of their biological potential beyond the structures directly accessible from Nature.

◼ Required Research Field of Study
  - Organic chemistry and/or biochemistry and/or molecular biology or similar

◼ Description of Research Activities During the Program
  - Research on discovery and biosynthesis of microbial natural products

◼ Research Equipment or Software to be Used
  - Full range of chemical (e.g., MPLC, HPLC, MS, NMR, etc.), microbiological (e.g., fermenters, autoclaves, clean bench, etc.), and biochemical (gel electrophoresis, protein purification, PCR, etc.) equipment and respective software.

◼ Website
  - https://www.helmholtz-hips.de/de/forschung/teams/team/naturstoff-biotechnologie/

【15-C. Dr. Alexander Titz】

◼ Research Field
  - Infections are among the most pressing threats to humanity. Our reserach focuses on the medicinal chemistry and chemical synthesis of novel antiinfectives (See recent publications here https://scholar.google.de/citations?user=kJIobrcAAAAJ&hl ). The molecules you will synthesized will be analysed by you using State-of-the-art analytics device at our institute. Then, testing in biophysical assays and/or antimicrobial susceptibility testing will be employed to assess your molecules, where you will be able to assist in the assay testing.

◼ Required Research Field of Study
  - Chemistry or Pharmacy, with Focus Organic Chemistry

◼ Description of Research Activities During the Program
  - Synthesis of novel antiinfectives

◼ Research Equipment or Software to be Used
  - synthesis equipment, MPLC, HPLC, mass spectrometer, NMR spectrometer

  ※ any specific requirements or important information
    - must be able to communicate verbally in English, spoken English minimum B1

◼ Website
  - www.helmholtz-hips.de

【15-D. Dr. Anna K.H.Hirsch】

◼ Research Field
  - The Hirsch group adopts a target-based rational design strategy focusing on biologically relevant, often underexplored enzymes, transporters and regulators within bacterial and parasitic pathogens. The group employs a variety of biophysical methods to investigate compound–target interactions and has established several in vitro and cell-based assays for straightforward evaluation of novel anti-infectives and multiparameter optimisation.

(Our research and approach)

The antimicrobial resistance crisis urgently calls for the development of new antibacterial agents with novel modes of action. To address this, we adopt a target-based strategy focused on a diverse portfolio of biologically relevant, underexplored drug targets, including enzymes, transporters, and regulators within bacterial pathogens. These targets can be divided into two main categories: those that impair vital mechanisms within the bacteria, leading to their death (e.g., DXPS, ECF-T, DnaN), and pathoblockers which interfere with pathogenicity and virulence without affecting bacterial viability (e.g., ColH, LasB). The pathoblockers are believed to cause a lower rate of resistance development, whilst preserving the commensal microbiota.

We employ a range of hit-identification strategies, including structure- and fragment-based drug design, virtual screening, high-throughput screening and a variety of biophysical methods. In addition, we pioneer innovative protein-templated techniques like dynamic combinatorial chemistry and kinetic target-guided synthesis, to address key bottlenecks in drug discovery. We use classical and innovative medicinal-chemistry approaches to design, synthesize and profile the most promising inhibitors, enabling efficient subsequent multipara-meter optimization. Various in vitro and cell-based assays, the generation of in silico data, elucidation of the mode of action and the co-crystallization of selected compounds with their targets support the straightforward evaluation of novel anti-infectives and their further optimization.

◼ Required Research Field of Study
  - chemistry, pharmaceutical sciences, biology, microbiology

◼ Description of Research Activities During the Program
  1) design and Synthesis of several projects of inhibitors of antibacterial drug targets
  2) assay development and biological profiling of antibacterial agents

◼ Research Equipment or Software to be Used
  1) synthetic organic chemistry and analytical lab
  2) biology lab

◼ Website
  - https://www.helmholtz-hips.de/en/research/teams/team/drug-design-and-optimisation/

【15-E. Dr. Mariia Nesterkina】

◼ Research Field
  - Our research focuses on the design, synthesis, and application of thermotropic liquid-crystal (LC) materials for advanced pharmaceutical and biomedical technologies. At the interface of pharmaceutical chemistry, organic chemistry, materials science, and pharmaceutical technology, we develop innovative bio-based LC systems that respond to physiological stimuli and enable next-generation drug-delivery solutions.

Specifically, we create nature-inspired thermotropic liquid crystals derived from molecules such as cholesterol, plant sterols, and terpenoids.
By combining organic synthesis with modern formulation science, we engineer LC-based materials that can change their structure, optical behavior, or permeability in response to temperature or infection-related cues.

These materials are integrated into polymer-dispersed LC films, smart wound-care scaffolds, and nanofiber systems to achieve controlled, on-demand delivery of anti-infective drugs and real-time visual monitoring of wound conditions. The work spans the full development chain: from molecular design and synthesis, characterization of mesophases, and physicochemical/mechanical analysis, to drug release studies, skin-permeation experiments, and prototype fabrication.

This interdisciplinary field offers students training in:
organic synthesis of LC materials
formulation and processing of smart biomaterials
microscopy, thermal analysis, and rheology
polymer science and nanofiber fabrication
drug-delivery technologies and skin-barrier research

◼ Required Research Field of Study
  - Chemistry, Pharmaceutical Sciences, Biology, Microbiology

◼ Description of Research Activities During the Program
  - Synthesis and basic characterization of thermotropic liquid crystals.
    Preparation and evaluation of LC-based materials, including 3D bioprinting.
    Conducting cell assays and microbiological tests.

◼ Research Equipment or Software to be Used
  - Organic synthesis equipment (fume hood, heating/stirring systems, distillation and purification setups)
    Thermal analysis instruments (DSC)
    Polarized light microscope for LC characterization
    3D bioprinter for fabrication of LC-based materials
    Cell culture facilities (biosafety cabinet, CO₂ incubator, microscope)
    Microbiology equipment (incubators, colony counter, spectrophotometer)

◼ Website
  - https://www.helmholtz-hips.de/en/

◼ Research Field
  1) Theme#1: Machine Vision for Humanoid and Legged Robots
  2) Theme#2: Emergent Energy-Efficient Gaits for Elastic Bipedal Robots
  3) Theme#3: Head, Hand, and Sensory System for Humanoid Robots

『Theme#1: Machine Vision for Humanoid and Legged Robots』

[Position Overview]: We are seeking a passionate intern to assist in the development of fundamental technologies for the perceptual capabilities of humanoid robots, with a focus on robot vision using machine learning (AI) methods. This role offers a unique opportunity to work with state-of-the-art robotics technology and gain hands-on experience in vision-based intelligent locomotion and navigation. The successful candidate will Gain practical experience with state-of-the-art humanoid robots, enhance skills in machine learning, computer vision, and robotics, and contribute to pioneering research in a collaborative and dynamic setting.

[Key Responsibilities]:
• Learn and understand the existing vision and locomotion systems of DLR's humanoid robots.
• Develop and implement machine learning algorithms for object recognition and segmentation, state estimation, and simultaneous mapping and localization (SLAM).
• Contribute to the creation of real-time vision-based world representations for humanoid robots.
• Test and refine vision-based algorithms to improve robot navigation and interaction capabilities.
• Collaborate with the robotics team to integrate and optimize vision systems within the overall robot control framework. 

[Qualifications]:
• Currently enrolled in a degree program in Computer Science, Electrical Engineering, Robotics, or a related field.
• Knowledge of machine learning and AI methods, with experience in relevant tools and frameworks (e.g., TensorFlow, PyTorch).
• Familiarity with computer vision techniques and technologies.
• Strong programming skills in languages such as Python, C++, or MATLAB.
• Excellent problem-solving abilities and a keen interest in robotics and AI.
• Strong communication skills in English and the ability to work both independently and as part of a team. 

『2) Theme#2: Emergent Energy-Efficient Gaits for Elastic Bipedal Robots』

[Position Overview]: The intern will contribute to research focused on achieving human-like, energy-efficient locomotion in bipedal robots equipped with elastic elements. Human walking and running are known to minimize metabolic and mechanical work by exploiting pendulum-like exchanges of kinetic and potential energy during walking, and elastic energy storage during running—principles rigorously characterized in the classic work of Cavagna and Kaneko on mechanical efficiency. This project aims to translate these mechanisms into robotic systems by identifying gait patterns that emerge from energy-based optimization rather than relying on predefined gait templates. The position offers hands-on experience with numerical optimization, simulation environments, and experimental validation on a hardware prototype.

[Key Responsibilities]:
• Study mechanical work and efficiency in human walking and running, with emphasis on energy exchange and elastic storage mechanisms
• Use and improve an optimization framework that generate efficient bipedal gaits by minimizing mechanical energy use.
• Develop algorithms that switch between emerging gait patterns as speed or conditions change.
• Analyze energy flow throughout the gait cycle and design cost functions that promote human-like efficiency.
• Validate optimized gaits in simulation and on existing robotic hardware.
• Evaluate locomotion performance using metrics such as cost of transport, mechanical work, and robustness across terrain.
• Document results and support dissemination in reports or publications. 

[Qualifications]:
• Enrolled in a degree program in Robotics, Mechanical Engineering, Electrical Engineering, Computer Science, or a related field.
• Programming skills in Python; familiarity with optimization, control, or machine learning is beneficial.
• Interest in human locomotion, biomechanics, compliant mechanisms, and energy-efficient motion.
• Ability to work analytically and experimentally across simulation and hardware tasks.
• Strong communication skills in English and the ability to work both independently and as part of a team. 

『Theme#3: Head, Hand, and Sensory System for Humanoid Robots』

[Position Overview]: The successful internship student will contribute to the development of the neck and head systems for our humanoid robots. Additionally, the intern will support improvements to other parts of the humanoid robot, such as the foot and leg mechanisms. This role offers a unique opportunity to engage in the entire process from kinematics design to hardware and software integration, gaining hands-on experience in robotics engineering and design. This will enhance skills in mechanical design, fabrication, and system integration while working in a dynamic and collaborative research environment.

[Key Responsibilities]:
• Assist in the kinematics design for humanoid and legged robots.
• Create detailed 3D CAD models of the neck, head, foot, and leg components.
• Participate in the fabrication and testing of new parts.
• Integrate hardware and software with the current humanoid system to ensure seamless operation.
• Create robot simulation environment with the robot model representations such as URDF
• Low-level software integration
• Collaborate with the robotics team to troubleshoot and optimize the neck, head, foot, and leg systems. 

[Qualifications]:
• Currently enrolled in a degree program in Mechanical Engineering, Robotics, Electrical Engineering, or a related field.
• Understanding of kinematics and mechanical design principles.
• Hands-on experience with fabrication and prototyping.
• Experience with 3D CAD modeling software (experience on CREO is plus), and ROS/ROS2.
• Programming skills in languages C++, and Python, and Matlab.
• Strong communication skills in English and the ability to work both independently and as part of a team.

◼ Required Research Field of Study
  - Please clearly indicate the interested theme in the application.
    1) Theme#1: Machine Vision for Humanoid and Legged Robots
    2) Theme#2: Emergent Energy-Efficient Gaits for Elastic Bipedal Robots
    3) Theme#3: Head, Hand, and Sensory System for Humanoid Robots

『Theme#1: Machine Vision for Humanoid and Legged Robots』
[Qualifications]:
• Currently enrolled in a degree program in Computer Science, Electrical Engineering, Robotics, or a related field.
• Knowledge of machine learning and AI methods, with experience in relevant tools and frameworks (e.g., TensorFlow, PyTorch).
• Familiarity with computer vision techniques and technologies.
• Strong programming skills in languages such as Python, C++, or MATLAB.
• Excellent problem-solving abilities and a keen interest in robotics and AI.
• Strong communication skills in English and the ability to work both independently and as part of a team.

『2) Theme#2: Emergent Energy-Efficient Gaits for Elastic Bipedal Robots』
[Qualifications]:
• Enrolled in a degree program in Robotics, Mechanical Engineering, Electrical Engineering, Computer Science, or a related field.
• Programming skills in Python; familiarity with optimization, control, or machine learning is beneficial.
• Interest in human locomotion, biomechanics, compliant mechanisms, and energy-efficient motion.
• Ability to work analytically and experimentally across simulation and hardware tasks.
• Strong communication skills in English and the ability to work both independently and as part of a team.

『Theme#3: Head, Hand, and Sensory System for Humanoid Robots』
[Qualifications]:
• Currently enrolled in a degree program in Mechanical Engineering, Robotics, Electrical Engineering, or a related field.
• Understanding of kinematics and mechanical design principles.
• Hands-on experience with fabrication and prototyping.
• Experience with 3D CAD modeling software (experience on CREO is plus), and ROS/ROS2.
• Programming skills in languages C++, and Python, and Matlab.
• Strong communication skills in English and the ability to work both independently and as part of a team.

◼ Description of Research Activities During the Program
  - Please clearly indicate the interested theme in the application.
  1) Theme#1: Machine Vision for Humanoid and Legged Robots
  2) Theme#2: Emergent Energy-Efficient Gaits for Elastic Bipedal Robots
  3) Theme#3: Head, Hand, and Sensory System for Humanoid Robots

『Theme#1: Machine Vision for Humanoid and Legged Robots』

[Position Overview]: We are seeking a passionate intern to assist in the development of fundamental technologies for the perceptual capabilities of humanoid robots, with a focus on robot vision using machine learning (AI) methods. This role offers a unique opportunity to work with state-of-the-art robotics technology and gain hands-on experience in vision-based intelligent locomotion and navigation. The successful candidate will Gain practical experience with state-of-the-art humanoid robots, enhance skills in machine learning, computer vision, and robotics, and contribute to pioneering research in a collaborative and dynamic setting.

[Key Responsibilities]:

• Learn and understand the existing vision and locomotion systems of DLR's humanoid robots.
• Develop and implement machine learning algorithms for object recognition and segmentation, state estimation, and simultaneous mapping and localization (SLAM).
• Contribute to the creation of real-time vision-based world representations for humanoid robots.
• Test and refine vision-based algorithms to improve robot navigation and interaction capabilities.
• Collaborate with the robotics team to integrate and optimize vision systems within the overall robot control framework.

 『2) Theme#2: Emergent Energy-Efficient Gaits for Elastic Bipedal Robots』

[Position Overview]: The intern will contribute to research focused on achieving human-like, energy-efficient locomotion in bipedal robots equipped with elastic elements. Human walking and running are known to minimize metabolic and mechanical work by exploiting pendulum-like exchanges of kinetic and potential energy during walking, and elastic energy storage during running—principles rigorously characterized in the classic work of Cavagna and Kaneko on mechanical efficiency. This project aims to translate these mechanisms into robotic systems by identifying gait patterns that emerge from energy-based optimization rather than relying on predefined gait templates. The position offers hands-on experience with numerical optimization, simulation environments, and experimental validation on a hardware prototype.

[Key Responsibilities]:
• Study mechanical work and efficiency in human walking and running, with emphasis on energy exchange and elastic storage mechanisms
• Use and improve an optimization framework that generate efficient bipedal gaits by minimizing mechanical energy use.
• Develop algorithms that switch between emerging gait patterns as speed or conditions change.
• Analyze energy flow throughout the gait cycle and design cost functions that promote human-like efficiency.
• Validate optimized gaits in simulation and on existing robotic hardware.
• Evaluate locomotion performance using metrics such as cost of transport, mechanical work, and robustness across terrain.
• Document results and support dissemination in reports or publications.

[Qualifications]:
• Enrolled in a degree program in Robotics, Mechanical Engineering, Electrical Engineering, Computer Science, or a related field.
• Programming skills in Python; familiarity with optimization, control, or machine learning is beneficial.
• Interest in human locomotion, biomechanics, compliant mechanisms, and energy-efficient motion.
• Ability to work analytically and experimentally across simulation and hardware tasks.
• Strong communication skills in English and the ability to work both independently and as part of a team. 

『Theme#3: Head, Hand, and Sensory System for Humanoid Robots』

[Position Overview]: The successful internship student will contribute to the development of the neck and head systems for our humanoid robots. Additionally, the intern will support improvements to other parts of the humanoid robot, such as the foot and leg mechanisms. This role offers a unique opportunity to engage in the entire process from kinematics design to hardware and software integration, gaining hands-on experience in robotics engineering and design. This will enhance skills in mechanical design, fabrication, and system integration while working in a dynamic and collaborative research environment.

[Key Responsibilities]:
• Assist in the kinematics design for humanoid and legged robots.
• Create detailed 3D CAD models of the neck, head, foot, and leg components.
• Participate in the fabrication and testing of new parts.
• Integrate hardware and software with the current humanoid system to ensure seamless operation.
• Create robot simulation environment with the robot model representations such as URDF
• Low-level software integration
• Collaborate with the robotics team to troubleshoot and optimize the neck, head, foot, and leg systems.

◼ Research Equipment or Software to be Used
  - Please clearly indicate the interested theme in the application.
    1) Theme#1: Machine Vision for Humanoid and Legged Robots
    2) Theme#2: Emergent Energy-Efficient Gaits for Elastic Bipedal Robots
    3) Theme#3: Head, Hand, and Sensory System for Humanoid Robots

『Theme#1: Machine Vision for Humanoid and Legged Robots』
• Knowledge of machine learning and AI methods, with experience in relevant tools and frameworks (e.g., TensorFlow, PyTorch).
• Familiarity with computer vision techniques and technologies.
• Strong programming skills in languages such as Python, C++, or MATLAB.

『2) Theme#2: Emergent Energy-Efficient Gaits for Elastic Bipedal Robots』
• Programming skills in Python; familiarity with optimization, control, or machine learning is beneficial.
• Experience in robot dynamic simulators: Mujoco, Isaac Sim/Lab

『3) Theme#3: Head, Hand, and Sensory System for Humanoid Robots』
• Experience with 3D CAD modeling software (experience on CREO is plus)
• ROS/ROS2.
• Programming skills in languages C++, and Python, and Matlab.
• Hands-on experience with and 3D print fabrication and prototyping. 

※ any specific requirements or important information
  - Please clearly indicate the interested theme number in the application and describe the research plan for the selected theme.

◼ Website
  - https://www.dlr.de/en/rm

※ 16번 연구소의 경우, 지원하고자 하는 연구주제(Theme 1,2,3) 기재 필수

◼ Research Field
  - microbiological researches, microbial genomic and microbial molecular biology

◼ Required Research Field of Study
  - microbiological background and knowledge, bioinformatic experiences in microbiology

◼ Description of Research Activities During the Program
  - participating our ongoing projects (TransEvo or LipoBac), preparing a munuscript.

◼ Research Equipment or Software to be Used
  - Linux and R studio

   ※ any specific requirements or important information
      - passion and a willingness to take on new challenges

◼ Website
  - mri.bund.de

◼ Research Field
  - Materials science. Failure mechanisms of advanced semiconductor devices using in situ electron microscopy

◼ Required Research Field of Study
  - Materials Science

◼ Description of Research Activities During the Program
  - Conduct mechanical testing on the semiconductor devices. Operating advanced electron microscopies

◼ Research Equipment or Software to be Used
  - Python (optional)

◼ Website
  - http://iam.kit.edu/mmi/

◼ Research Field
  - Urban and peri-urban forests (UPFs) are essential for human well-being, and the WHO (UN) considers UPFs as critical infrastructure in a post-Covid society. However, the health of trees in UPFs and the provision of ecosystem services from urban forests are threatened by the effects of climate change and urbanization. The person will be involved in the ongoing URBORETUM project.

In the URBORETUM project, we aim to uncover the ecological processes associated with the decline in tree health in urban forests and the provision of ecosystem services in different types of UPFs. We also aim to quantify the impact of UPFs on human brain functions and psychological well-being and improve current urban forest management practices by translating research findings into practice. In the process, we will develop a modern, technology-based, socially accepted, and cost-effective urban forest inventory system.

The URBORETUM project comprises a diverse transdisciplinary consortium. The research work is divided into a total of five work packages, which are managed independently by each partner.

The TreeEcos work package, led by the “Sylvanus” research group at the Institute for Technology Assessment and Systems Analysis at the Karlsruhe Institute of Technology (KIT), focuses on investigating the changing structure and composition of urban forests. This involves examining how the availability of nutrients, light, and water influences the ecological processes of trees.

The TreePulse work package, also based at KIT, is concerned with combining functional ecology and remote sensing. It examines the health of individual tree species in urban areas and investigates how the vitality of trees decreases under drought conditions. In addition, an irrigation experiment is carried out in collaboration with the Karlsruhe Horticultural Office to show how to optimize the irrigation of urban trees in order to reduce the decline in tree health caused by drought.

As part of the TreeCare work package, dendroecological studies are carried out at the University of Freiburg, including analysis of the isotopic composition of dendrochronological cores. This allows to draw conclusions about physiological processes in trees during or after extreme climatic events.

The TreeNeuro work package, led by the Central Institute of Mental Health in Mannheim, is dedicated to identifying critical factors of urban forests and their influence on the well-being of city dwellers. It also investigates the individual mental and physiological benefits of urban trees and the underlying neural and physiological mechanisms.

Our municipal partner, the Horticultural Office of the City of Karlsruhe, supports the research in the URBORETUM project with its own work package (TreeCityKA).

In addition, URBORETUM is accompanied by own work packages (TreeInspect and TreeTwin) of two leading companies in the field of wood and tree analysis and digital urban forestry. The intern will be involved TreeEcos, TreePulse, and TreeTwin.

Project website: https://www.urboretum.de
Research group “Sylvanus – Increasing resilience and reducing trade-offs during urban and peri-urban forest transformations” (SYL) website: https://www.itas.kit.edu/english/rg_syl.php

◼ Required Research Field of Study
  - Background in the field of environmental or natural sciences such as Geography, Geoecology, Biology, Environmental sciences and engineering, or relevant studies

◼ Description of Research Activities During the Program
  - Assist in exploring trade-off analysis of urban forestry scenarios, focusing on cultural, regulating, supporting, and provisioning ecosystem services.
  - Support GIS-based spatial analysis (ArcGIS Pro) for mapping and preliminary calculations of environmental benefits under different planting strategies.
  - Contribute to linking digital twin concepts with climate adaptation and urban planning frameworks, under guidance from the research team.
  - Provide assistance in organizing data for statistical analysis (R/SPSS) to evaluate stakeholder preferences and integrate findings into decision-making frameworks.

◼ Research Equipment or Software to be Used
  -  Microsoft 365: Excel, PowerPoint, Word
  - Statistical Analysis: SPSS, R (if applicable)
  - GIS & Environmental Tools: ArcGIS Pro, i-Tree Eco (if applicable)
  - greehill urban forest digital twin platform (if applicable)

  ※ any specific requirements or important information
      - Preferred start date: August 2026 (negotiable).

◼ Website
  - https://www.itas.kit.edu/english/

◼ Research Field
  - The Manufacturing Technology Instiute – MTI of RWTH Aachen actively shapes the transformation process towards future-proof, digitally networked and sustainable production. As one of the largest production technology institutes, we see ourselves as having a responsibility to strengthen industrial value creation with a clear focus on economic efficiency, sustainability and resilience and in this way make our contribution to a future worth living.

As a part of MTI, the Department of Forming Technology stands for excellent research, hands-on development and individual consulting in the field of forming technology. With our many years of experience and in- depth expertise, we offer a wide-ranging portfolio of customized services that are specifically tailored to the requirements of a wide variety of industries and project partners.

Our aim is to develop innovative solutions along the entire forming technology process chain - from material selection and process design through to implementation in real production environments. We not only use state-of-the-art simulation technologies and experimental facilities, but also draw on the interdisciplinary cooperation within production engineering at RWTH Aachen University in order to make optimum use of synergies.

Our focus is on the targeted implementation of your requirements, the identification of new potential and the increase of efficiency, quality and profitability in your production processes. Regardless of whether you are a small or medium-sized company or an international industrial group - we accompany you in partnership on the way from the idea to series production.

Focus of work:

  * System, product and process optimization
  * Material charactrization
  * Tribology analysis
  * Tool wear monitoring
  * Error identification during complex forming processes

◼ Required Research Field of Study
  - Mechanical Engineering, Production Engineering, or any comparable fields

◼ Description of Research Activities During the Program
  - Support in planning and conducting experimental investigations
  - Evaluation of experimental investigations through metrological analyses (e.g., microscopy)
  - Learning and applying script-based analysis of measurement signals or data (Python)
  - Learning and applying simulation of forming processes (FEM)

◼ Research Equipment or Software to be Used
  - Python, LabVIEW, DIAdem, 3D Profilometer from Keyence, Abaqus, Forge

   ※ any specific requirements or important information
      - on-site work & active participation on social events are preferred

◼ Website
  - https://www.mti.rwth-aachen.de/

◼ Research Field
  - Our workgroup ISTS (Innovations in Sociotechnical Systems) envisions well-aligned social and technical systems that facilitate innovation and thereby support the transition toward a sustainable biobased economy. Its mission is to contribute to the generation and institutionalization of knowledge on the interplay of subsystems in support of an innovative, circular, inclusive, and cumulative biobased economy. To this end, holistic strategies, processes, as well as structures for collaboration, governance, and learning are co-designed and implemented jointly with stakeholders, employing innovative methods and tools to foster sustainable transformations toward a biobased economy.

◼ Required Research Field of Study
  - Bioenergy, Environmental Engineering, Economics, Policy studies or other relevant studies

◼ Description of Research Activities During the Program
  - The objective of the project is to compare different innovation pathways for biogas technology, with a particular focus on interdependences between policy settings, innovation focuses and business model development, and on understanding the implications for technological development and value propositions.

Two sub-projects are available for students to choose from:
  (1) Development of policy recommendations for the sustainable and equitable deployment of biogas technologies in Korea.
    Planned research activities include:
      - Conducting a literature review on existing policy instruments for biogas technology
      - Supporting data collection (e.g., expert interviews, focus group discussions)
      - Supporting the comparative analysis of biogas-related policies and institutional arrangements, and their interactions with biophysical and natural environments as well as socio-economic conditions in Germany and Korea
      - Identifying and assessing the potential societal and environmental impacts of biogas policies in Korea.

  (2) Analysis of different innovation pathways for biogas technology across selected countries
    Planned research activities include:
      - Data collection (e.g., indicators of innovation environments relevant to biogas technology development)
      - Supporting archetype analysis to show how innovation environments shape different trajectories of technology development and deployment

The activities can be adapted based on the shared interests of the student and the host.

◼ Research Equipment or Software to be Used
  - Sub-project (1): Qualitative data analysis software (e.g., Atlas.ti, Nvivo),
  - Sub-project (2): knowledge in R or fsQCA is an advantage.

   ※ any specific requirements or important information
    Your qualifications
      - Strong interest in research at the intersection of society and technology
      - (desirable) Previous experience in policy and governance analysis
      - Excellent communication and teamwork skills

     What we offer
      - A competent and research-driven working environment
      - Access to national and international research projects and networks
      - Opportunities to participate in colloquia and academic events

◼ Website
  - www.atb-potsdam.de

◼ Research Field
  - The performance of modern fuel cells and electrolyzers is controlled by complex dynamics of chemical solutions undergoing diffusion and chemical reactions on the surface of porous materials.

These systems are fascinating since many physical processes spanning from bubble nucleation to transport across porous materials occur at the same time and in an highly out-of-equilibrium environment.

Understanding the dynamics of such complex systems leads to two main outcomes:
  - improve the performance fuel cells and electrolyzers can significantly boost the energy transition that we are facing
  - provide insight into fundamental questions about the physics of out of equilibrium systems

Within my team we aim at a theoretical description of fuel cells/electrolyzers as well as confined chemical reactors in general. We pursuit these objective by a melange of techniques. Tailored molecular dynamics and Lattice Boltzmann simulations are used to tackle the microscopic details, whereas we approach the mesoscopic scale with analytical models. When needed, hybrid numerical/analytical approaches and machine learning tools are developed.

◼ Required Research Field of Study
  - Statistical Mechanics, fluid dynamics

◼ Description of Research Activities During the Program
  - develop numerical approaches to study the reactive fkows within porous materials

◼ Research Equipment or Software to be Used
  - pyhthon, Fortran

◼ Website
  - https://www.hi-ern.de/en/research/dynamics-of-complex-fluids-and-interfaces-1/dynamics-of-confined-fluids

◼ Research Field
  - The Institute of Functional Materials for Sustainability focuses on developing functional materials that enable a more sustainable future. Our research is centered on converting waste into higher value resources and designing environmentally responsible material systems.

Major research directions include:
· Biological conversion of waste using bacteria and other microorganisms to synthesize useful fuels and chemicals.
· Biodegradable plastics and sustainable polymers, including the development of eco-friendly 3D-printing materials from industrial byproducts such as lignin.
· Renewable-energy-driven recycling and upcycling, especially CO₂ conversion and the re-utilization of diverse waste streams to support circular material flows.

The institute supports the principles of a circular economy through interdisciplinary research combining chemistry, biology, materials science, and engineering. Our laboratories are equipped with extensive analytical and experimental facilities, providing a strong environment for systematic material development and performance evaluation.

◼ Required Research Field of Study
  - We welcome students majoring in materials science, energy engineering, chemical engineering, polymer science, or bio-related fields, etc.
    Students with a data science background are also welcome, especially for data analysis of scientific results.
    A background in electrochemistry, organic chemistry, polymers, or biotechnology is helpful.
    In particular, students with experience in electrochemistry or organic chemistry may find it easier to join our projects.

◼ Description of Research Activities During the Program
  - The specific topic will depend on the student’s major, but in general, students will work on developing technologies to convert bio-waste materials
(such as glycerol or lignin), nitrates, or carbon dioxide into value-added products using various methods.

Under the supervision of a postdoctoral researcher or PhD student, students will learn how to conduct experiments, analyze data, and understand related scientific processes.

◼ Research Equipment or Software to be Used
  - Our institute has a wide range of equipment required for the research areas mentioned above.
    Visiting students will receive training on the instruments and will be allowed to learn and use the equipment directly during their project.

    ※ any specific requirements or important information
      - Applicants should be able to communicate in basic English and have a motivated and proactive attitude toward research.
        We welcome students who are eager to learn and actively participate in the project.

◼ Website
  - https://www.hereon.de/institutes/functional_materials_for_sustainability/index.php.en

◼ Research Field
  - Our research group studies hazards and related surface processes across a wide range of environments, from mountain regions to coastal areas and even deep oceans, over different time scales. Our work has wide topics ranging from earthquake and tsunami, storm and hurricane, landslide and debris flow, to flood and paleo-flood. We use various tools and methods, including field surveys, remote sensing, environmental seismology methods, processes-based modelling, and data science methods, including machine learning to understand the physical processes behind all these natural hazards.

◼ Required Research Field of Study
  - Geoscience/Physics/Data science/Computer Science

◼ Description of Research Activities During the Program
  - As an interdisciplinary and diverse research group, we can offer many opportunities for the participants with various interesting projects. There are two main types of tasks: method-development-oriented and application-oriented tasks. For a method-oriented, the participant could learn and develop physics-based machine learning methods for solving partial differential equations or investigating physics. An application-oriented participant could work on earth science or hazard-related research in the project using methods borrowing from computer vision, natural language processing, or signal processing. The participant will involve and support us in developing open-source data science model toolkits for the earth science and hazard science communities. Feel free to contact us if you have any questions about the projects or bring your own ideas. We specifically welcome applicants from under-presented groups and female applicants.

◼ Research Equipment or Software to be Used
  - We use the High-Performance Computing infrastructure, including GPU and CPU clusters from our section, GFZ or Helmholtz association, as our main computation resource. For programming languages, we have used different mainstream languages, including Fortran, C, C++, Python, R, Matlab, and Julia, depending on the project. Regarding the data science model, we develop and use open-source platforms such as Scikit-learn, Tensorflow, and PyTorch.

    ※ any specific requirements or important information

       - The student should have experience in coding and basic Knowledge of data science.

◼ Website
  - https://www.gfz.de/en/section/earth-surface-process-modelling/overview

◼ Research Field
  - Cell Biology of Pancreatic Beta Cells

◼ Required Research Field of Study
  - molecular or cell biology, biochemistry

◼ Description of Research Activities During the Program
  - determined in discussion with the student

◼ Research Equipment or Software to be Used
  - determined in discussion with the student

◼ Website
  - www.islets.de

◼ Research Field
  - The diversity of cell types, tissues, and organs arises from complex interactions among genetic networks. Perturbations in these interactions can cause or drive the onset of disease, and understanding these early molecular events is essential for predicting disease trajectories and identifying opportunities for early therapeutic intervention.

To investigate these processes, we pursue an interdisciplinary approach, integrating biochemistry, molecular biology, and data science. Recently, we developed an inexpensive, do-it-yourself, high-resolution, and open-source spatial transcriptomics method, Open-ST, to quantify gene expression directly within tissue samples (Schott, Leon-Perinān, Splendiani et al., Cell; 2024, STAR Protocols). We now routinely generate spatial transcriptomics data, providing a highly informative readout of cellular communication within tissues/tumors, as well as of cellular responses to perturbations, such as disease-associated mutations, viral infections, or environmental stressors including microplastics. Computational analyses, including machine-learning strategies, are combined with experimental testing to generate and validate mechanistic insights.

We are actively working on adapting and extending open-ST, to support our specific research questions. This includes, for example, the optimization for using formalin-fixed paraffin-embedded tissues, to enable the use of biobanked material, as well as the integration with long-read sequencing technologies for isoform-level analyses.

Much of our work relies on patient-derived material—supported by extensive collaborations with the Charité hospital Berlin—as well as patient-derived organoid models. Current disease areas under investigation include cancer (triple-negative breast cancer, non-small cell lung cancer, neuroblastoma) and neurodegenerative disorders.

Collectively, our work aims to uncover how gene regulatory processes shape human health and disease, with the goal of informing earlier and more precise strategies for disease intervention.

◼ Required Research Field of Study
  - RNA biology, (spatial) transcriptomics

◼ Description of Research Activities During the Program
  - The student’s research activities will focus on refining Open-ST sequencing library preparation through targeted depletion and/or selective
enrichment strategies. Open-ST is a flexible, high-resolution, and open-source spatial transcriptomics method, developed in our lab (Schott, León
Periñán, Splendiani et al., Cell, 2024; STAR Protocols, 2024). While it provides an unbiased view of a tissue’s gene expression in space, it also captures highly abundant or non-informative RNA species (e.g., rRNA, mitochondrial transcripts, non-variable genes), reducing the effective sequencing depth of more informative transcripts.

The student will survey the available depletion and enrichment strategies, together with the supervisor, and define a specific methodological focus. The project will involve testing and benchmarking selected approaches, with the aim of improving the recovery of low- and moderate-abundance transcripts that often define subtle cell states or regulatory processes.

Approaches may include probe- or bead-based depletion strategies as well as CRISPR/Cas-guided degradation. In addition to depletion, the student may explore amplicon-based enrichment approaches to increase the representation of specific transcripts within spatial cDNA libraries. For long-read sequencing of Open-ST libraries, the student may additionally evaluate Oxford Nanopore adaptive sampling, which enables real-time enrichment or depletion of molecules during sequencing. The student will assess how these depletion or enrichment steps influence overall transcript complexity, spatial barcode retention, and UMI distribution, as well as assess potential biases they may introduce.

Overall, the student’s work will contribute directly to the broader effort in the lab to increase the information content and efficiency of Open-ST libraries and will support protocol improvements currently under development.

◼ Research Equipment or Software to be Used
  - The project can have a computational and/or experimental focus, depending on the student’s background and interests.

    Equipment: Cryostat, qPCR instruments, PCR cyclers, brightfield microscope, automated gel electrophoresis machine (Tapestation/Bioanalyzer), PippinHT automated agarose gel for size selection

    Software: Spacemake and openst (based on python and bash, https://github.com/rajewsky-lab/spacemake, https://github.com/rajewsky-lab/openst), Scanpy and scverse, potentially porechop for Adapter removal and demultiplexing of Oxford Nanopore reads, potentially DASHit for guideRNA design for CRISPR-depletion strategy (Dynerman, Lyden, et al., BioRxiv, 2020)

◼ Website
  - https://www.mdc-berlin.de/n-rajewsky

◼ Research Field
  - The Ernst Ruska-Centre for Microscopy and Spectroscopy with Electrons in Jülich hosts one of the strongest research groups internationally in aberration-corrected high-resolution transmission electron microscopy method development and applications to problems in solid state research. The Ernst Ruska-Centre operates more than 15 electron microscopes, including a next generation FEI PICO chromatic aberration corrected transmission electron microscope with a resolution of 50 picometers and a double biprism dedicated transmission electron microscope for magnetic imaging using off- axis electron holography.

◼ Required Research Field of Study
  - Materials science, physics or a related field.

◼ Description of Research Activities During the Program
  - Electron microscopy of materials.

◼ Research Equipment or Software to be Used
  - Advanced transmission electron microscopes.

◼ Website
  - https://er-c.org/

◼ Research Field
  - At the INW Institute Division INW-1 “Catalytic Interfaces”, the focus is on the elementary processes on the catalyst surface during the de(hydrogenation) of hydrogen storage molecules. Our focus is on maximizing productivity, efficiency, and selectivity in order to optimize performance, mitigate losses, and degradation and reduce costs. The aim is to understand reaction and degradation mechanisms at the molecular level at the catalytically active interfaces in order to further extend the life cycle of the storage molecules through optimized catalyst materials. Another aim is to avoid the use of precious metal components, e.g. by developing new types of alloy catalysts. We are also researching new storage molecules, e.g. with reduced dehydrogenation energy or of biogenic origin, for which the elementary processes on the catalyst surface, suitable material combinations and relevant degradation mechanisms must be clarified and fundamentally understood. In addition to the focus topic of chemical hydrogen research and the corresponding focus molecules (e.g. methanol, DME, ammonia, methane, formic acid, LOHC), we also conduct research in the fields of electrochemical energy storage, water desalination, and direct lithium extraction.

In this context, we at INW-1 conduct basic and application-oriented research on mechanisms and processes at the atomic to mesoscale level with a focus on interfacial and transport phenomena. We work closely with the other Institutes of INW and Forschungszentrum Jülich to accelerate technology development in a holistic way. We interpret the gained fundamental understanding in the context of the material and device performance and thus contribute to predictable and scalable knowledge for rational design and new concepts for improved materials and processes. To investigate the corresponding phenomena, we use and develop X-ray and neutron-based methods across time and length scales and apply corresponding advanced (big) data analytics tools and machine learning. In this context, we operate corresponding advanced infrastructure and measurement equipment.

◼ Required Research Field of Study
  - Physical chemistry, Analytic chemistry, Catalysis, Electrochemistry, or Spectroscopy

◼ Description of Research Activities During the Program
  - Joining fundamental researches on hydrogen storage (electro)catalysis with real-time/operando advanced spectroscopy/microscopy

◼ Research Equipment or Software to be Used
  - Potentiostat, FT-IR spectroscopy, Raman spectroscopy, Mass spectrometry

    ※ any specific requirements or important information
      - INW-1 at Forschungszentrum Julich is actively developing advanced analytic methodologies with real-time monitoring of catalytic systems under realistic conditions. Anyone interested in understanding real structural dynamics of catalytic systems is welcome!

◼ Website
  - https://www.fz-juelich.de/de/inw/unsere-bereiche/inw-1

https://www.fz-juelich.de/en/inw/overview-inw-1/catalytic-interfaces-for-chemical-hydrogen-storage-inw-1/fundamentals-of-chemical-hydrogen-storage/catalytic-interfaces 

【29-A. Dr. Vanessa Maybeck】

◼ Research Field
  - For neuro-electronic hybrid systems such as neural implants or prostheses, the interface between the neuronal network and engineered surfaces is of critical importance. An ideal neural interface should form a stable, adhesive link between neurons and an external device, while still allowing active communication with the cells. To date, micro- and nanoscale test systems have employed advanced materials such as carbon nanotubes, silicon nanowires, conducting polymers, graphene, or organic–inorganic hybrids to promote neuronal growth and enable signal recording or stimulation. In parallel, upconversion nanoparticles (UCNPs) have emerged as promising tools for activating light-sensitive proteins in optogenetics.

Optogenetics makes use of light-sensitive proteins—originally found in algae or microbes—that can be genetically expressed in mammalian neurons to control ion currents using light. Depending on the protein type, neurons can be either depolarized or hyperpolarized. However, the short-wavelength light (blue or green) that these proteins typically respond to suffers from poor tissue penetration and can cause phototoxic effects during prolonged illumination. This challenge motivates the search for strategies that deliver precise, localized light stimulation while minimizing tissue damage.

UCNPs provide an elegant solution. These nanomaterials absorb near-infrared (NIR) light—which penetrates tissue deeply and is far less phototoxic—and converts it into higher-energy visible light locally at the target cell. They combine several advantageous properties: low toxicity, high photostability, large Stokes shifts (the energy difference between absorbed and emitted light), narrow emission spectra, and minimal tissue autofluorescence.

Recent research continues to expand UCNP performance and versatility. New synthesis methods have improved crystallinity and upconversion efficiency (Farva et al., 2025). Polymer-coated UCNPs have enhanced biocompatibility and functional tunability for biomedical applications (de Freitas Silva et al., 2025). UCNPs are now even being explored for powering molecular motors using NIR light—highlighting the broad potential of these nanomaterials (Sheng et al., 2025).

Despite this progress, UCNPs have not yet been widely used to functionalize neural implants for optogenetic stimulation. Current approaches often rely on implanting separate optical components or multiple devices, which can increase surgical trauma and reduce the implant’s electrical performance. Our research explores a more integrated strategy: using UCNPs both as light-emitting stimulation sites and as adhesive bridges between neurons and implant surfaces. This dual role could preserve electrical recording capability while adding optical control. Importantly, UCNPs generate far fewer photons than direct laser illumination, helping to reduce phototoxicity in living cells.

Integrating UCNPs into neural implants presents several engineering challenges. Achieving efficient optogenetic stimulation requires close proximity between the UCNPs and light-sensitive proteins, demanding precise control of the device–UCNP and UCNP–cell interfaces. Optimization of UCNP surface chemistry is therefore crucial to promote strong cell adhesion and stability. In this research stay, UCNPs will be used to combine optical and electrical functionality in next-generation neural interfaces. With ongoing advances in synthesis, coating, and biointegration, these materials open exciting opportunities for safer, smarter neurotechnologies.

◼ Required Research Field of Study
  - Chemistry or Chemical Engineering or Electrophysiology

◼ Description of Research Activities During the Program
  - Assist in synthesis of upconversion nanoparticles and their characterization with optogenetic devices.

◼ Research Equipment or Software to be Used
  - The project will use amplifiers and software developed by the institute as well as sterile technique for primary cell culture, microfabrication tools, and chemical synthesis equipment including a Schlenk-line.

◼ Website
  - https://www.fz-juelich.de/de/ibi/ibi-3

【29-B. Dr. Hans-Joachim Krause】

◼ Research Field
  - The Magnetic Field Sensors group is working on frequency mixing magnetic detection of nanoparticles for biosensing application, for instance magnetic immunoassays, and on low field nuclear magnetic resonance. The aim is to establish magnetic label-based immunoassays which employ the highly specific interaction between antigenes and antibodies in conjunction with magnetic nanoparticle markers for the detection and quantification of specific biomolecules. Research Topics include measuring the magnetic response of magnetic nanoparticles by Frequency Mixing Magnetic Detection (FMMD), and magnetic particle actuation by applying a magnetic gradient field with magnetic tweezers.

◼ Required Research Field of Study
  - Physics or Electrical Engineering or Informatics or similar

◼ Description of Research Activities During the Program
  - Research on Frequency Mixing Magnetic Detection and development of dedicated measurement instrumentation

◼ Research Equipment or Software to be Used
  - Custom-made measurement instrumentation, Python software

◼ Website
  - https://www.fz-juelich.de/en/ibi/ibi-3/organization/magnetic-field-sensors

◼ Research Field
  - The Spatial Economics team explores how energy transition processes affect economies on various regional levels, analyzing their implications for stakeholders and offering insights to inform science and society. With foundations in economics, econometrics, and policy assessment, we develop tools for providing levers that facilitate smooth energy system transition pathways aligned with climate goals and stakeholder demands. Applying cross-sectional and panel data for, e.g., Germany, the EU, and international contexts, our analyses give insights into e.g. regional economic expansion potential of renewables, multi-regional decision analyses, and provide distributive assessments for energy technologies from an economic perspective. Application focuses lie in wind power and general effects of renewables after end-of-life (circular economy), the economic effects of carbon dioxide removal and sustainable transition of energy intensive industries. Our audience includes scientists, policymakers, and decision-makers seeking informed strategies for navigating energy transitions and transformation processes.

◼ Required Research Field of Study
  - Economics, Econometrics, Applied Mathematics, Environmental Science, Energy Science, Social Sciences, Sustainability, or related programs

◼ Description of Research Activities During the Program
  - Collaboratively formulate a research question aimed at conducting a self-directed project within the team’s research scope. Contribute to analyses, research, and writing to produce and submit a research paper. Participate in literature reviews, attend and engage in regular team and institute meetings, and actively contribute to project discussions

◼ Research Equipment or Software to be Used
  - Laptop computer including necessary software will be provided. Possibility to use the institute's cluster server and energy system model.

    ※ any specific requirements or important information
      - Willingness to work in a highly interdisciplinary research environment

◼ Website
  - https://www.fz-juelich.de/en/ice/ice-2

◼ Research Field
  - Infectious disease research, virology

◼ Required Research Field of Study
  - Virology

◼ Description of Research Activities During the Program
  - Respiratory syncytial virus (RSV) is the most common cause of acute lower respiratory tract infection in infants and young children worldwide and remains a major clinical challenge for the elderly and immunocompromised. While vaccines and monoclonal antibodies have recently expanded preventive options, our understanding of host-intrinsic factors that determine disease severity is still incomplete. In particular, human genetic variation affecting innate antiviral immunity is emerging as a key determinant of severe RSV outcomes.

This project aims to identify and mechanistically dissect genetic risk factors that compromise antiviral defense against RSV. Building on our recent genome-wide CRISPR/Cas9-based survival screen, we have identified critical host genes that modulate RSV infection at the cellular level. Using RSV reporter viruses, live-cell imaging, and interferon-responsive reporter systems, we demonstrated that tyrosine kinase 2 (TYK2), a central component of type I interferon signaling, plays a pivotal role in restricting RSV replication. Loss or functional impairment of TYK2 leads to attenuated antiviral signaling and enhanced viral replication in vitro.

Extending these findings, we now focus on coding TYK2 variants identified in human populations, particularly in children with severe RSV disease. These naturally occurring variants provide a unique opportunity to link human genetics with viral pathogenesis. Loss-of-function mutations and hypomorphic alleles will be functionally characterized to uncover how specific molecular defects weaken interferon-mediated antiviral responses. A broad spectrum of state-of-the-art cell biological, molecular, and virological techniques will be employed to address these questions.

By integrating human genetic data with mechanistic infection biology, this project seeks to uncover fundamental principles of RSV host defense. It offers an exciting and intellectually stimulating research environment for international Master’s students eager to gain hands-on experience at the interface of virology, immunology, and functional genomics.

◼ Research Equipment or Software to be Used
  - FACS, next generation sequencing, live cell imaging, confocal microscopy, etc.

◼ Website
  - https://twincore.de/labs/pietschmann-lab

◼ Research Field
  - [Molecular structural dynamics using ultrafast spectroscopies]

Elementary chemical reactions in biomolecular systems occur on the femtosecond (fs) timescale, accompanied by significant structural rearrangements within the molecular framework. These reactions are initiated by optical excitation with UV/vis light, and their reactivity is strongly influenced by the molecular architecture and the surrounding environment. We investigate electronic structural dynamics using fs-resolved probing techniques, starting with tailored model systems:

1. Cis–Trans Isomerisation. Cis–trans isomerisation underlies light-sensory functions in retinal-based photoreceptors. While most chromophores absorb in the visible range, a few opsins in insects and birds respond to UV light. In contrast to the visible rhodopsins calculations indicate that triplet states of UV-sensitive opsins are nearly isoenergetic to the optically excited singlet state, which therefore should play a role in their dynamic reaction path.

2. Spin State Change in Metal-Organic complexes. Oxidation-state changes govern catalytic cycles in metalloenzymes such as hydrogenases and cytochrome complexes, tightly coupled to electron charge flow. To emulate these redox-driven processes, we study photo-excited states of Ni(II) Schiff-base-like complexes. Here, ligand substitution with electron-affine groups modulates the charge transport behaviour and access to the triplet channel, which switches the molecule’s luminescence on or off, offering potential applications including fluorescent tags.

To capture the dynamic reaction pathways, we use femtosecond-resolved spectroscopy techniques: UV/vis light probes the valence electronic structures, while X-rays probe detailed element-specific structural changes. The UV/vis measurements are conducted at home laboratories, while X-ray measurements are performed at Synchrotron/XFEL facilities.

◼ Required Research Field of Study
  - Physical chemistry, Nonlinear optics, X-Ray Spectroscopy, or similar fields

◼ Description of Research Activities During the Program
  - Femtosecond transient absorption measurements, X-ray absorption spectroscopy measurements

◼ Research Equipment or Software to be Used
  - Femtosecond laser systems, Synchrotron/FEL light source facilities, python

    ※ any specific requirements or important information
      - Experience with laser system would be beneficial.

◼ Website
  - Institute website: https://desy.de/
  - Group website: https://www.physik.uni-hamburg.de/en/iexp/gruppe-bressler/personen.html

◼ Research Field
  - KIT is one of the largest research institutions worldwide and provides access to state-of-the-art research facilities. The Institute for Advanced Membrane Technology (IAMT) is part of the Faculty of Chemical and Process Engineering. The research team is highly international, and English is used as the primary language for both oral and written communication.

IAMT contributes to addressing key societal challenges through research that spans from membrane material development to the application of membrane processes for water treatment. The scope of scientific activities focuses on the removal of micropollutants from water (e.g., steroid hormones, PFAS, herbicides, inorganic contaminants, and nanoplastics). A core challenge at IAMT is managing small sample volumes, large numbers of samples, and the extremely low concentrations of micropollutants remaining after treatment. Extending solution chemistries from synthetic to real waters at environmentally relevant concentrations represents a significant achievement of the institute.

The IAMT laboratories are equipped with multiple state-of-the-art filtration systems ranging from laboratory to full-scale modules. A wide range of membrane processes is available, including microfiltration, ultrafiltration, nanofiltration, and electrodialysis, as well as reactive membrane techniques such as adsorption, photocatalysis, and electrocatalysis, complemented by batch experiments.

Moreover, the institute is equipped with a comprehensive suite of high-quality analytical tools for the quantification of micropollutants at trace levels typical of natural water matrices. These include LC-OCD/OND, FFF, ICP-MS, GC-MS, IC, UHPLC, LC-MS/MS, TOC analyzers, and methods for detecting radiolabeled micropollutants at concentrations as low as 0.1 ng/L. The coupling of selected analytical techniques enables a fundamental understanding of solute–solute interactions during membrane transport, as well as in-depth elucidation of adsorption and degradation mechanisms.

In addition, IAMT offers extensive facilities for material characterization (TGA, SURPASS, contact angle measurements, membrane stability testing, accelerated aging, impedance spectroscopy, and SEM sample preparation) and membrane fabrication (doctor blade, coagulation bath, electrospinning, and dip coating).

IAMT also integrates membrane technology with renewable energy in collaborative projects, developing mobile, robust systems designed for autonomous operation in rural areas and developing countries, which are field-tested in various regions, including Africa.

At IAMT, we train ambitious researchers in a first-class research environment with modern, well-equipped laboratories. We offer students career-oriented training through innovative, interdisciplinary research; we teach advanced scientific expertise and methods; and we share our passion for solving real-world problems.

◼ Required Research Field of Study
  - Candidates should be enrolled in a studies program in Chemical Engineering, Process Engineering, Environmental Engineering, or an equivalent field. Applicants should be naturally curious, eager to learn, and strongly motivated to conduct research.

While we welcome students from a broad range of related disciplines, we expect commitment, a willingness to learn, and active engagement in the opportunities offered at IAMT. A basic understanding of water chemistry, water treatment processes, and membrane technology is considered an asset. Applicants should demonstrate proficiency in English and a proven ability to learn and work independently. Familiarity with OriginLab (for data analysis and graph preparation) and EndNote (for literature management), as well as an interest in contributing to the preparation of a scientific publication, will be considered advantageous.

The examples of Master Projects are:
1) Steroid hormone micropollutant removal with nanofiber−nanoparticle composite membranes
2) Fate of nanoplastics in membrane processes
3) Urea degradation via membrane photolysis
4) Steroid hormone micropollutant degradation by photocatalytic membrane reactors

More info: https://www.iamt.kit.edu/118.php

◼ Description of Research Activities During the Program
  - The type and number of experiments depend on the specific project and are defined in a concept note prepared prior to the start of the project. Projects at IAMT typically include around 50 planned experiments, developed in consultation with the supervisors (postdoctoral researchers).

 A comprehensive literature review on the topic will be conducted. The student will be responsible for performing laboratory experiments (and sample analyses in specific cases), maintaining accurate lab records, identifying and labeling samples, analyzing results, and performing meaningful error analysis. The obtained results will be critically analyzed, summarized in the concept note, and regularly presented during individual and group meetings to discuss findings and address any challenges encountered during the research process.

◼ Research Equipment or Software to be Used
  - The specific research equipment will depend on the individual project; however, a broad range of advanced experimental techniques is available at IAMT. These include microfiltration, ultrafiltration, nanofiltration, and electrodialysis, as well as reactive membrane processes such as adsorption, photocatalysis, and electrocatalysis, complemented by batch experiments. Students receive comprehensive training on all instruments relevant to their research and have continuous access to supervision and technical consultation. Samples collected during the project are typically analyzed by supervising postdoctoral researchers, while students are actively involved in sample preparation and preliminary analyses. Experimental setups at IAMT are equipped with LabVIEW software for automated data acquisition, and OriginLab software is used for data analysis and graph preparation.

※ any specific requirements or important information

  - At IAMT, students are offered a structured masterclass that develops key research skills essential for their work. The course covers topics such as filtration protocols, error analysis, introduction to analytical methods, data visualization and graphing, as well as research integrity and good scientific practice. The preparation of a scientific publication may be considered if the student makes a significant academic contribution to the project. Authorship decisions are made collaboratively within the supervisory team, in accordance with institutional guidelines. All research data generated during the project remain the intellectual property of IAMT and may not be published, shared, or transmitted to third parties without prior written approval from the Institute Director.

◼ Website
  - https://www.iamt.kit.edu/

◼ Research Field
  - The research field is "Materials Tribology". About 23 % of humanity's energy usage is wasted overcoming friction forces. We therefore strive to develop alloys which lead to less friction and wear and thereby will drastically reduce CO2 emissions. In order to be able to do so, we have to understand how metals and alloys react to a frictional load. We do so by performing elementary friction experiments, mainly on copper and copper alloys, and then have a detailed look at the changes to the materials by high-resolution electron microscopy.

◼ Required Research Field of Study
  - Materials Science, Mechanical Engineering, Solid State Physics

◼ Description of Research Activities During the Program
  - Sample preparation
    Frictional testing
    Microscopy of the worn surfaces, including high-resolution profilometry
    Perhaps electron microscopy

◼ Research Equipment or Software to be Used
  - Metallographic grinding and polishing machines
    White-light profilometer
    Reciprocating tribometers
    optical mircoscopy
    Perhaps DualBeam focused ion beam and scanning electron microscope

     ※ any specific requirements or important information
        - An open mind and an eagerness to learn.

◼ Website
  - https://www.iam.kit.edu/zm/index.php

◼ Research Field
  - autonomous driving, cooperative systems, robotics, vehicular communications

◼ Required Research Field of Study
  - computer science, human factors, robotics

◼ Description of Research Activities During the Program
  - Participation in ROBOT POLICEMAN project

◼ Research Equipment or Software to be Used
  - humanoid robots, bicycles, cameras, radars, lidars, traffic lights

◼ Website
  - https://cas.aifb.kit.edu/

◼ Research groups
Prof. Caroline Barisch, Prof. Kay Grünewald, Prof. Meytal Landau, Prof. Maria Rosenthal, Prof. Holger Sondermann, Dr. Roland Thünauer, Prof. Maya Topf, Prof. Charlotte Uetrecht, and details can be found here: https://www.cssb-hamburg.de/ 

◼ Research Field
  - Infectious diseases are a global threat that costs many lives and have a significant impact on society. The key to effectively fighting infectious diseases is gaining a detailed understanding of the underlying molecular mechanisms of various pathogens. At the Centre for Structural Systems Biology (CSSB), scientists study the structure and function of pathogens, such as viruses, bacteria, parasites and amyloids, and their interactions with the host. In the process, CSSB’s fundamental research seeks to enable the identification of targets for interventions.

CSSB is a joint initiative of ten leading research institutions in Germany that are dedicated to advancing molecular infection biology. CSSB serves as a collaborative research hub, integrating cutting-edge methods such as structural biology, artificial intelligence and multi-modal imaging. CSSB’s state-of-the-art scientific infrastructure includes four core facilities: for  
i) protein production, ii) sample preparation, characterization & high-throughput crystallization, iii) advanced light and fluorescence microscopy, and iv) cryo-EM. Centrally located on the Science City Hamburg-Bahrenfeld campus, CSSB’s infrastructures are complemented by direct access to DESY’s X-ray beamlines, enabling our scientist to use a sophisticated combination of structural biology approaches.

◼ Required Research Field of Study
  - Biology, Biochemistry, Chemistry, Microbiology, Molecular Life Sciences, or a related field

◼ Description of Research Activities During the Program
  - Work on innovative research projects in molecular structural infection biology

◼ Research Equipment or Software to be Used
  - At CSSB, research groups offering internships in this program investigate bacteria, viruses, and microbial and antibacterial amyloids, as well as host–pathogen interactions with a focus on infection research. Students will be trained the necessary technologies and software on site that will be specific in the groups of interest. Projects range from structural prediction using AI-based software to super-resolution and cryo-EM (live-cell or quantitative microscopy), structural mass spectrometry analyses and wet-lab experiments, depending on the student’s choice among participating CSSB research groups and project construction. 

◼ Website
  - https://www.cssb-hamburg.de/

【36-B. Hannover Medical School at CSSB Hamburg - Dr. Jens B. Bosse】

◼ Research Field
  - The Bosse Lab investigates the molecular architecture and dynamics of virus–host interactions, with a particular focus on herpesvirus infection. We combine structural systems virology, advanced imaging, and AI-driven computational modeling to understand how viral proteins assemble, remodel cellular environments, and drive key steps of the infection cycle.

Our work spans scales—from high-resolution structural predictions (AlphaFold-Multimer, cryo-EM/CLEM) to live-cell and super-resolution microscopy that captures viral processes in real time. We map viral interactomes, identify molecular interfaces, and use mutational energetics and binder design to test mechanistic hypotheses directly in living cells.

By integrating computational predictions with quantitative imaging, cell-free interaction assays, and functional virology, the Bosse Lab aims to uncover conserved principles of viral replication, identify vulnerabilities in viral machineries, and ultimately enable rational design of antiviral strategies.

◼ Required Research Field of Study
  - Computational Biology, Structural Biology, Virology, Cell Biology

◼ Description of Research Activities During the Program
  - Computational and/or lab work depending on students interests

◼ Research Equipment or Software to be Used
  - Python, structural prediction software, molecular biology/virology equipment depending on students choice

◼ Website
  - www.bosse-lab.org
  - www.virusfolds.org
  - www.herpesfolds.org

◼ Research Field
  - We work on mechanisms, diagnosis and treatment options for patients with (rare) autoimmune neuroinflammatory disorders like multiple sclerosis, neuromyelitis optica and MOGAD

◼ Required Research Field of Study
  - Basic or clinical neuroimmunology

◼ Description of Research Activities During the Program
  - Wetlab or clinical research, depending on the type of project

◼ Research Equipment or Software to be Used
  - N/A

◼ Website
  - https://www.mdc-berlin.de/paul