◼ Research Field
  - The Bonn Department is a group of physicists, chemists, and engineers working to exploit intrinsic molecular motion to learn about the natural world. To this end, we use a combination of cutting-edge spectroscopies and microscopies to probe questions regarding physico-chemical coupling in systems relevant to biology and materials science. Our three main themes are water, biomolecules, and charge-carrier dynamics. The research explores both fundamental aspects and applications in environmental processes, biophysics, and energy conversion. To achieve these goals, cutting-edge, laser-based spectroscopic tools have been developed and implemented. The work spans terahertz spectroscopy on semiconductors and fundamental research on water. In both lines of research, innovative techniques have been developed that allowed the detailed study of charge carrier dynamics and molecular water behaviour at interfaces, including nanoconfined water.

◼ Required Research Field of Study
  - Chemistry, Physics

◼ Description of Research Activities During the Program
  - Research projects in line with intern's skills and knowledge

◼ Research Equipment or Software to be Used
  - Individual, to be evaluated and determined according to intern's skills and knowledge

◼ Website
  -  https://www.mpip-mainz.mpg.de/de/bonn

◼ 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