30.08.2026, Academic staff
For our AI-Assisted Healthcare Lab at TUM School of Medicine and Health, we are seeking an outstanding PhD student (f/m/d) to advance the theoretical and methodological foundations of medical deep learning. The project focuses on novel self-supervised objectives, information geometry, mitigating representation bias for rare pathological findings, and building next-generation multimodal foundation architectures. Full-time, TV-L E13, 100%, fixed-term for 3+ years.
Position PhD Student (100%) Remuneration TV-L E13 (Fully Funded, fixed-term for 3+ years) Field Representation Learning, Foundation Models & Medical AI Location Munich, GermanyFor our AI-Assisted Healthcare Lab at TUM School of Medicine and Health, we are seeking an outstanding PhD student (f/m/d) to advance the theoretical and methodological foundations of medical deep learning and develop next-generation foundation model architectures for precision medicine.
Self-supervised objectives like masked autoencoders and joint-embedding predictive architectures bias representations toward frequent patterns. Rare but informative signals get suppressed because the training loss does not reward encoding them. In medicine, rare findings are often the most important, as a small change can be the difference between normal and pathological. We want to understand this bias and correct it.
This is a fully funded position (TV-L E13, 100%) for a PhD student with a strong background in mathematics, computer science, or machine learning. The work has a strong focus on developing new objectives or new architectures for medical deep learning and on new ways to measure what representations contain or miss. The position is embedded in a well-funded, multi-year research project providing a unique multimodal and longitudinal setting for this research.
The work will combine methodological development with large-scale experiments, aiming for contributions at leading machine learning and computer vision venues such as NeurIPS, ICML, ICLR, CVPR, and MICCAI, as well as high-impact medical journals.
The PhD will be embedded at TUM University Hospital, offering direct access to large-scale multimodal clinical datasets, high-end GPU and storage infrastructure, international research collaborations, and dedicated funding for international conference participation.
The PhD candidate will be supervised by:
We are looking for candidates with:
Please submit your application including a CV, cover letter, and complete academic transcripts (Bachelor’s and Master’s) via email directly to:
The position is suitable for disabled persons. Disabled applicants will be given preference in case of generally equivalent suitability, aptitude and professional performance.
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Kontakt: [email protected], [email protected], [email protected]
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The Technical University of Munich is a public research university for engineering, natural sciences, life sciences, medicine, and economics.