Technical University of Munich
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4 months ago
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PhD in Foundation Models and Digital Patient Twins for Precision Medicine at Technical University of Munich Technical University of Munich in Germany
Degree Level
PhD
Field of study
Oncology
Funding
Full-time TV-L E13 PhD position for 48 months. Includes access to large-scale multimodal clinical datasets, high-end GPU infrastructure, conference travel, workshops, and short research stays at partner institutions. The post is funded through the TWIN-X Horizon Europe consortium.
Deadline
Expired
Country
Germany
University
Technical University of Munich
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About this position
Technical University of Munich / TUM University Hospital is hiring a PhD student for research on foundation models and digital patient twins in oncology and cardiovascular medicine.
The position is embedded in TWIN-X, a Horizon Europe consortium with 18 European partners. The project works with large-scale multimodal clinical data, including radiology, pathology, genomics, laboratory values, clinical notes, and longitudinal patient trajectories from several thousand patients.
Research topics include multimodal and longitudinal patient modelling, representation learning, self-supervised and contrastive pretraining, masked modelling, generative objectives, cross-attention models, mixture-of-experts systems, temporal transformers, and JEPA-style models. Own research ideas are strongly encouraged.
The role offers full-time TV-L E13 funding for 48 months, access to high-end GPU infrastructure (including H100, H200, and B300 servers), large-scale storage, conference travel, workshops, and short research stays at partner institutions across Europe.
Eligibility highlights: a strong Master's degree in computer science, mathematics, physics, engineering, medical informatics, biomedical engineering, or a related field; excellent quantitative background; strong Python and deep learning skills (preferably PyTorch); and solid foundations in machine learning, statistics, linear algebra, and model evaluation. Excellent English is required; German and prior medical AI experience are helpful but not mandatory.
Supervision is provided in the medical AI environment of TUM University Hospital and the Department of Diagnostic and Interventional Radiology, with Prof. Dr. Lisa Adams, PD Dr. med. Keno Bressem, and Dr. rer. nat. Cosmin I. Bercea involved.
To apply, email your materials to [email protected] and include a cover letter, CV, complete Bachelor and Master transcripts, degree certificates, and optional publication/code/reference materials. Applications without complete transcripts cannot be fully assessed.
Funding details
Full-time TV-L E13 PhD position for 48 months. Includes access to large-scale multimodal clinical datasets, high-end GPU infrastructure, conference travel, workshops, and short research stays at partner institutions. The post is funded through the TWIN-X Horizon Europe consortium.
What's required
Master's degree with excellent grades in computer science, mathematics, physics, engineering, medical informatics, biomedical engineering, or a related field; very strong undergraduate and graduate record, especially in quantitative subjects; strong Python skills and experience with deep learning frameworks, preferably PyTorch; solid foundations in machine learning, statistics, linear algebra, and model evaluation; interest in foundation models, representation learning, multimodal learning, generative AI, or longitudinal modelling; ability to work independently and learn difficult methods quickly; excellent English skills. German and prior experience in medical AI are helpful but not required.
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Professors
Professor of Radiology, Deputy Director Radiology
Germany
Research Interests
Cardiology
Statistics
Biomedical Engineering
Physics
Mathematics
Make your next move.
Prepare your application
Review drafts and confirm requirements with the university.