Partner of our mobility programmes:

Max Delbrück Center

Understanding how life works: At the MDC, scientists are investigating the molecular basis of health and disease—from personalized medicine to AI-supported diagnostics.

Through HIDA’s mobility programs, data science talents at MDC can contribute to pioneering research projects in the field of biomedicine. The goal: to gain a deeper understanding of the human body.

 

 

About the Helmholtz Association

The Helmholtz Association

The Helmholtz Association is Germany’s largest scientific organization. Our cross-cutting research programs connect the 18 Helmholtz research centers. 

Each center has its own scientific focus areas and infrastructures. The research is thematically structured into six fields:

  • Energy
  • Earth & Enviroment
  • Health
  • Information
  • Aeronautics, Space & Transport
  • Matter

 

The Max Delbrück Center for Molecular Medicine (MDC) is one of the world’s leading research institutions in the field of biomedical sciences. Interdisciplinary teams work together to decode the complex processes of the human body. Their goal is to understand the factors that regulate—or disrupt—the balance within cells, organs, and the entire organism. This knowledge paves the way for new approaches to disease prevention, early detection, and personalized treatment.

Research priorities

  • Systems medicine and cardiovascular diseases
  • Genes, cells, and cell-based medicine
  • Molecular processes and therapies
  • Integrative biomedicine
  • Cancer research and immunotherapies

The sites

The sites

Main site: Berlin-Buch

Additional site: Berlin-Mitte

Research collaborations:

  • Experimental and Clinical Research Center (ECRC)

  • Berlin Institute of Health (BIH) at Charité

  • German Centre for Cardiovascular Research (DZHK)

MDC expertise in the field of Data Science and AI

The MDC applies cutting-edge AI methods and data-driven approaches to analyze complex biological systems. Researchers develop innovative algorithms for disease prediction, therapy optimization, and the analysis of large medical datasets.

  • AI-powered pattern recognition in genomic and proteomic data
  • Automated image analysis for cancer diagnostics
  • Machine learning for modeling disease progression
  • Development of simulation models for personalized therapies
  • Multimodal data integration to enhance biomedical research

Around 1,200 employees from 64 countries work at the MDC.

Application

Would you like to conduct research and work at MDC? Then apply now for the HIDA Mobility Program!

Apply now!

Please contact your potential supervisor by email before applying to propose and discuss a research project. Only submit your application after this has been clarified.

You can find more information about the application requirements here.

Learn more!

Note for external applicants:

If you have any questions about application formalities or organizational procedures, please contact your home institution directly.

The Hosts at MDC

Get to know some of the hosts at MDC and learn more about their respective research based on data science.

Please note: The listed hosts represent only a selection of possible supervisors.

You are also welcome to independently contact other potential hosts at the center and coordinate your participation in the HIDA Mobility Program directly with them.

If you have any questions, please send an email to: hida@helmholtz.de

Are you interested in becoming a Helmholtz host yourself and looking for support for your research project?
Then please also contact the above-mentioned email address.

Altuna Akalin
Bioinformatics and Omics Data Science

Contacts

Altuna Akalin
Bioinformatics and Omics Data Science

Short summary of your group's research: We have a broad interest in gene regulation, specifically transcriptional regulation and association of transcriptional regulation with epigenomics. We are aiming to use data intensive computational methods to uncover patterns in gene regulation relating to cell differentiation and complex diseases.    

        

What infrastructure, programs and tools are used in your group? HPC, statistical and machine learning tools implemented in Python or R

 

What could a participant of the HIDA Trainee Network learn in your group? How could he or she support you in your group? Participant can learn domain specific data processing techniques and provide support in machine learning applications.

Claudia Chien
Clinical Neuroimmunology

Contacts

Claudia Chien
Clinical Neuroimmunology

Short summary of your group's research: Our group follows a translational clinical research approach. This means that we try to transfer new developments and findings from basic research directly into clinical work. We mainly focus on research in multiple sclerosis and neuroinflammatory diseases, however the MRI Team within AG Neuroimmunology has several projects that investigate other disorders. These imaging analysis methods and techniques are translatable to many different central nervous system studies.          

 

What infrastructure, programs and tools are used in your group? Berlin Center for Advanced Neuroimaging, NeuroCure Clinical Research Center, Neuroimmunological Colloquium, Berlin Institute of Health, Bernstein Center for Computational Neurosciences

 

What could a participant of the HIDA Trainee Network learn in your group? How could he or she support you in your group?A guest researcher would learn how to investigate MRI parameters from clinical studies from real patients and volunteers. The researcher would be expected to support our group with set up of analysis pipelines of raw MRIs using high performance computing (https://www.hpc.bihealth.org/) resources and learn how to quality control clinically relevant data.

Laleh Haghverdi
Computational methodologies and omic analytics

Contacts

Laleh Haghverdi
Computational methodologies and omic analytics

Short summary of your group's research: We are a computational biology group working with a range of single-cell omic data modalities including proteomics, transcriptomics, epigenetics and genomics to study biological systems such as development, haematopoiesis or leukaemic stem cells and their niche.Establishment of efficient computational methodologies for analysis of large single-cell omic data sets, resolution of complex lineage trees, data integration and interpretation across multiple modalities and assays as well as mathematical formulation of the applied methods are of central interest in the group.            

 

What infrastructure, programs and tools are used in your group? Python, R, computational tools for single-cell data analysis

 

What could a participant of the HIDA Trainee Network learn in your group? How could he or she support you in your group? Hight-throughtput measurements of molecular states at the single-cell level are today accessible for biological and clinical studies, thanks to new and still evolving technological developments. Located in the cool central Berlin district, we are an interdisciplinary group trained in physics, mathematics, bioinformatics and molecular biology working together to address several aspects of computational analysis of such newly emerging datasets. We are interested in extending our machine learning and data science collaborations and contacts.

Jakob Metzger
Quantitative Stem Cell Biology

Contacts

Jakob Metzger
Quantitative Stem Cell Biology

Short summary of your group's research: We are an interdisciplinary group focusing on a quantitative understanding of human neurodevelopment using stem-cell derived organoids. Using machine learning to analyze the difference between normal and pathological processes, we aim to dissect the mechanisms of neurodevelopmental and neurodegenerative diseases.           

 

What infrastructure, programs and tools are used in your group? Python, R, machine learning

 

What could a participant of the HIDA Trainee Network learn in your group? How could he or she support you in your group? As an interdisciplinary group, we apply a range of computational tools to the  analysis of biological data, including imaging and genomics data.  Participants can learn data analysis techniques and provide support in developing new data science pipelines, such as machine learning applications.

Max Delbrück Center – Discovery for tomorrow's medicine

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