Computational Health Center
We develop novel computational tools powered by AI to accelerate discovery and translation. We apply cutting-edge computational methods to promote personalised health. Collaboratively, we develop predictive algorithms as well as mechanistic models to analyse molecular, imaging, and clinical data of human health and disease. We thus help to create innovative diagnostics and novel treatments for environmentally triggered diseases.
We develop novel computational tools powered by AI to accelerate discovery and translation. We apply cutting-edge computational methods to promote personalised health. Collaboratively, we develop predictive algorithms as well as mechanistic models to analyse molecular, imaging, and clinical data of human health and disease. We thus help to create innovative diagnostics and novel treatments for environmentally triggered diseases.
Our Research Areas
Discover Our Highlights
Upcoming Computational Health Seminars
Christian Ledig
15.01.2026
Host: Carsten Marr
Title: TBD
Time: 16.00 (CET)
Location: Hybrid
Anna Bauer-Mehren
29.01.2026
Host: Annalisa Marsico
Title: TBD
Time: 11.00 (CET)
Location: Hybrid
Alex Tong
02.02.2026
Host: Antonio Scialdone
Title: TBD
Time: 11.30 (CET)
Location: Hybrid
Ben Lehner
12.02.2026
Host: Ele Zeggini
Title: TBD
Time: 16.00 (CET)
Location: Hybrid
Michael Ingrisch
26.02.2026
Host: Carsten Marr
Title: TBD
Time: 16.00 (CET)
Location: Hybrid
Our Principal Investigators
Explainable Machine Learning
Zeynep Akata
Deep Federated Learning in Healthcare
Shadi Albarqouni
Helmholtz Pioneer Campus
Nico Battich
Data Science and Intelligent Systems
Stefan Bauer
Translation Genetics
Na Cai
Systems Genetics and Machine Learning
Paolo Casale
Biostatistics
Christiane Fuchs
Computational Epigenomics
Maria Colomé-Tatché
Machine Learning and Data Analytics
Björn Eskofier
Efficient Learning and Probabilistic Inference for Science (ELPIS)
Vincent Fortuin
Computational Molecular Medicine
Julien Gagneur
Genetic and Epigenetic Gene Regulation
Matthias Heinig
Computation and Machine Learning
Dominik Jüstel
Reliable AI
Georgios Kaissis
Reliable Machine Learning
Niki Kilbertus
Immunogenomics
Sarah Kim-Hellmuth
Medical Genomics
Janine Knauer-Arloth
Immunogenomics
Daniel Kotlarz
Integrative Genomics
Malte Lücken
Institute of AI for Health
Carsten Marr
Computational RNA Biology
Annalisa Marsico
Computational Biomedicine
Michael Menden
Computational Statistics and Data Science for Biological Systems
Christian Müller
Neurogenetic Systems Analysis
Konrad Oexle
AI for microscopy and computational pathology
Tingying Peng
Helmholtz AI
Marie Piraud
Multiomics for Disease Diagnostics
Holger Prokisch
Machine Learning in Biomedical Imaging
Julia Schnabel
Translational Immunoinformatics
Benjamin Schubert
Human-Centered AI
Eric Schulz
Physics and data-based modelling of cellular decision making
Antonio Scialdone
Machine Learning and Data Science
Hannah Spitzer
Pioneer Campus
Lara Urban
Machine Learning
Fabian Theis
Metabolomics
Rui Wang-Sattler
Dynamical Inference
Steffen Schneider
Institute of AI for Health
Ewa Szczurek
Precision Neuromedicine
Juliane Winkelmann / Barbara Schormair
Translational Genomics
Ele Zeggini
Accessible Biomedical AI Research
Sebastian Lobentanzer
Machine Learning for Biological Discovery
Michael Heinzinger
Our Institutes
Ewa Szczurek & Carsten Marr
Institute of AI for Health
Fabian Theis
Institute of Computational Biology
Zeynep Akata
Institute of Explainable Machine Learning
Eric Schulz
Institute of Human-Centered AI
Julia Schnabel
Institute of Machine Learning in Biomedical Imaging
Juliane Winkelmann
Institute of Neurogenomics
Eleftheria Zeggini
Institute of Translational Genomics
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Health AI Fellows (HAIF) Program
The newly established Health AI Fellows (HAIF) Program is dedicated to fostering independent, high-impact research in computational biomedicine and health-related AI. Our mission is to empower early-career postdoctoral scientists from computational, mathematical, engineering, and physical science disciplines by granting them early scientific independence to boldly address key challenges in computational biomedicine.
Recent advances in computation have transformed our understanding of molecular processes and their effects on health and disease. Breakthroughs in modeling, AI, and large-scale data analysis have reshaped biomedicine, enabling researchers to extract meaningful insights from increasingly complex biological datasets. As high-throughput technologies generate vast volumes of data, new challenges emerge in scale, management, analysis, and interpretation. Yet, these same developments open unprecedented opportunities to uncover complex biological mechanisms, predict system behavior, and understand pathophysiological processes. Despite remarkable progress, we are only beginning to tap into what computation and AI can achieve for human health.
By leveraging experimental, computational, and statistical approaches, the HAIF Program empowers fellows to explore new scientific frontiers that integrate data-driven and experimental methodologies. Working closely with experimental partners in Munich and beyond, fellows bring fresh perspectives to significant biological and biomedical challenges—stimulating innovation and driving the development of transformative solutions.
A Strategic Approach to Technological Readiness
Unlike traditional postdoctoral positions, HAIF fellows join the Computational Health Center (CHC) at Helmholtz Munich as independent early-career researchers with greater autonomy. Each fellow is mentored by two CHC Principal Investigators, or optionally by one PI and one external expert from industry or a start-up. With this support structure, fellows have the freedom to develop and apply comprehensive computational strategies to tackle pressing challenges in health research. The program emphasizes not only scientific discovery but also strategic progress toward higher technological readiness levels.
Fellowship Package and Support
The HAIF Program provides fellows with the resources needed to establish their independent research trajectory. Each package includes:
- A full-time postdoctoral position
- Dedicated budget for travel and open access publications
- Access to powerful computational infrastructure
- Funding for a student assistant
- Initial employment for two years, with the possibility of extension
- Support in identifying third-party funding opportunities and preparing grant proposals through the CHC Grant Management team
Fellows also receive full access to Helmholtz Munich’s platforms and core facilities and benefit from mentoring by CHC faculty and external partners. They are encouraged to engage with the vibrant research ecosystem across Helmholtz Munich, local universities, and regional collaborators, fostering a highly interdisciplinary and innovative environment.
The call for applications will open in mid-December!
Apply here
Networks and Affiliations
Contact
Head of Science Management & Administration, Institute of Computational Biology
anna.sacherspam prevention@helmholtz-muenchen.de
Ingolstädter Landstraße 1, 85764 Neuherberg
Building / Room: 58a, 105