PhD Position in Foundation Models for Medical Reasoning
100%, Basel, fixed-term
The research group led by Michael Moor is seeking to fill a PhD position focusing on medical reasoning with foundation models. We are looking for an ambitious candidate eager to conduct groundbreaking research in medical AI. Our goal is to advance the capabilities and faithfulness of medical reasoning models across diverse medical contexts. The successful candidate will join a cutting-edge research group that is pioneering medical foundation models, agent systems, and reasoning models.
Job Description
- Develop novel methods that advance the reasoning capabilities of medical foundation models (LLMs, MLLMs, and multi-agent systems).
- Design multimodal retrieval-augmentation strategies integrating EHRs, clinical guidelines, imaging databases, and other structured knowledge sources.
- Implement flexible memory and retrieval systems to support reasoning-chain generation and sequential decision-making in clinical tasks.
- Develop approaches to reduce hallucinations and improve reliability and robustness of medical AI systems, including adversarial robustness (in collaboration with SHS).
- Post-train and test-time scale multimodal foundation models at multiple scales.
- Co-develop a new benchmark for multimodal clinical reasoning and explainable sequential decision-making.
- Publish research results in top-tier ML venues (e.g., NeurIPS, ICML, ICLR) and premier biomedical journals (e.g., Nature Medicine, Nature Biomedical Engineering).
- Participate in collaborations across the MLCARE consortium (including funded secondments to a Max Planck Institute and Siemens).
- Engage in dissemination, open-source contributions, and knowledge-transfer activities.
Profile
- Master’s degree in Computer Science, AI, Machine Learning, Mathematics, Electrical Engineering, or a closely related field; or
- Master’s degree in Medicine (MD) with strong Python skills and some ML experience.
- Strong programming skills in Python and experience with modern ML stacks (PyTorch, HuggingFace, distributed training).
- Experience in LLMs, vision-language models, multimodal learning, or clinical NLP is highly welcome.
- For computational candidates: experience in large-scale ML training (multi-node setups, distributed training) is a strong advantage.
- Good computational engineering practices: version control, reproducible pipelines, batch job management, etc.
- Ability to work independently, contribute to team efforts, and communicate effectively in English.
- Prior research experience, publications, or industry ML experience are pluses but not required.
Workplace
Working within the Department of Biosystems Science and Engineering (D-BSSE) located in Basel, our environment is highly interdisciplinary and is embedded in a significant hub for medical and biomedical research and biotechnology.
We Offer
- A full-time, fully funded MSCA Doctoral Network position at ETH Zurich, one of the world's leading research universities.
- Our group is engaged with the ETH AI Center and SwissAI initiative, providing members access to a vibrant and world-class AI community.
- Access to cutting-edge computational resources, including large GPU clusters, and medical and biomedical collaborations.
- Membership in the Europe-wide MLCARE consortium for exchange and collaborations.
We Value Diversity and Sustainability
In line with our values, ETH Zurich encourages an inclusive culture. We promote equality of opportunity and value diversity while nurturing a working and learning environment that respects the rights and dignity of all our staff and students. Visit our Equal Opportunities and Diversity website to learn how we ensure a fair and open environment that allows everyone to grow and flourish. Sustainability is a core value for us, and we are consistently working towards a climate-neutral future.
Curious? So Are We.
We look forward to receiving your online application, including the following documents (concatenated into one PDF):
- CV
- Bachelor and Master transcripts
- Motivation letter (covering your motivation & fit for the program and the host lab)
- Letters of recommendation (if available, or a list of names that could provide references)
Apply online using the form below. Please note that only applications matching the job profile will be considered.
About ETH Zurich
ETH Zurich is one of the world's leading universities specialising in science and technology. Renowned for excellent education, cutting-edge fundamental research, and direct transfer of new knowledge into society, we foster an environment that inspires independent thinking and excellence. With over 30,000 people from more than 120 countries, we are located in the heart of Europe while forging connections globally to develop solutions for today's and tomorrow's global challenges.