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At Helmholtz Munich, we develop groundbreaking solutions for a healthier society in a rapidly changing world. We believe that diverse perspectives drive innovation. Through strong partnerships, we accelerate the transfer of new ideas from the lab to real-life applications, improving lives.
Helmholtz Munich is a leading European hub for AI in Health. By designing, developing and applying innovative AI models, we drive biomedical discovery to lay the foundation for technologies that transform medicine. Working hand in hand with experimental and clinical partners, we accelerate translation so that our research reaches society and improves people’s lives.
Join us at Helmholtz Munich’s Computational Health Center and make a difference as a
Principal Investigator (f/m/d) for (i) AI in Biomedicine or (ii) AI Foundations
We are looking for two outstanding researchers with a strong track record of advancing the state of the art in machine learning and its application to biology and medicine, with the ambition to build an internationally visible research group. The successful candidate will have the opportunity to shape a long-term research agenda, mentor junior researchers, and collaborate across disciplinary boundaries.
You will benefit from being part of the Helmholtz Association – Europe’s largest Research Organisation – with its unique Helmholtz AI platform.
Managing Director Mike Frieser:
"We believe that diversity is the key to groundbreaking research and innovative solutions. Our flexible working models and remote options create a supportive environment for balancing work and family life. For us, contributing to a healthier society in such an inspiring workplace is truly meaningful."
Possible research directions include (but are not limited to)
For AI in Biomedicine:
Representation learning for complex biomedical data
Large language models for patient records and multi-omics
Generative AI for therapeutic and molecular design
Sensor data integration and analysis
AI for clinical trials
Fair, robust and trustworthy AI for clinical applications
For AI foundations:
Explainable, interpretable and causal machine learning
Reinforcement learning, planning and sequential decision-making
Scaling, compression, and efficient training of multimodal and foundation models
Self-supervised, contrastive, continual, curriculum, and lifelong learning
Agentic foundation models, tool use, self-improving or self-updating AI models
Representation learning, cross-modal alignment, and multimodal learning
Your profile
Excellent PhD and/or postdoctoral record with outstanding scientific achievements, international research experience, and publications in relevant journals and/or in top-tier machine learning venues (e.g., NeurIPS, ICML, ICLR, CVPR, ICCV, ECCV).
Background in machine learning and AI, computer science or related fields
Demonstrated commitment to high-impact research that is translational research or inspired by unmet clinical needs or improving public health outcomes
Experience in interactive collaboration across technical, clinical, and/or industry domains
A visionary and implementable research agenda that advances or leverages cutting-edge AI to solve critical problems
Commitment to establishing and developing your own research group with a clear scientific profile
Exceptional communication, organizational, mentorship and leadership skills
Benefits
Scientific Resources: State-of-the-art infrastructure and Core Facilities
International Staff Service: Support with the relocation and integration process in Germany
Recreation: 30 days annual leave, flexi days, plus public holidays
Family Support: On-site kindergarten, holiday care, care for the elderly
Grow as a leader: Personalized and diverse development programs
Health Promotion: Sports, company doctor, mental health initiatives
Our offer
An exceptional opportunity for scientific independence and to establish yourself at the forefront of applied AI using singular biomedical datasets
A generous start-up package (salary, positions, and running costs) equivalent to the scope and duration of an ERC Starting Grant
A five-year PI position with tenure option
A vibrant, international, highly collaborative, and interdisciplinary research environment in Munich – one of the world’s most liveable cities
Integration into Helmholtz Munich’s Computational Health Center and Helmholtz AI, as well as Munich’s thriving digital health ecosystem, supported by the Munich Center for Machine Learning (MCML), ELLIS Munich (with the opportunity to join the ELLIS Society), and the M1 Munich Medicine Alliance, the university hospitals of TUM and LMU, and the German Centers for Health Research (https://deutschezentren.de/)
If you fulfill all the requirements, you may be eligible for a salary grade of up to E15. Social benefits are based on the Collective Wage Agreement for Public-Sector Employees (TVöD). The position has an (initial) fixed term of 5 years, with the possibility of moving to a permanent contract.
Interested in applying?
For scientific questions regarding the positions, please contact Prof. Carsten Marr, Director of the Institute of AI for Health at CHC ([email protected]). For operational or administrative questions, please contact Anna Sacher, CHC Director of Operations ([email protected]), who will be happy to help. Our recruiting is decentralized – your application will be reviewed directly by the specialist department in which you could work in the future.
The documents are only required upon recruitment and can be submitted at a later date.
We are committed to promoting a culture of diversity and welcome applications from talented people regardless of gender, cultural background, nationality, ethnicity, sexual identity, physical abilities, religion or age. Qualified applicants with physical disabilities will be given preference.
Regarding these positions, we specifically welcome applications from female scientists. Helmholtz Munich is a certified equal opportunity employer with a family-friendly research environment, flexible hours and remote working options, dual-career opportunities and a child-care facility on campus.
