Publisher
source

Technical University of Munich

Top university

PhD Position in Foundation Models and Digital Patient Twins for Precision Medicine Technical University of Munich in Germany

Degree Level

PhD

Field of study

Computer Science

Funding

Full funding available
Country flag

Country

Germany

University

Technical University of Munich

Social connections

How do I apply for this?

Sign in for free to reveal details, requirements, and source links.

Apply for this position

Keywords

Computer Science
Biomedical Engineering
Radiology
Deep Learning
Biology
Mathematics
Precision Medicine
Medical Science
Genomic
Digital Pathology
Statistics
Physics

Suggested positions

About this position

PhD position at the Technical University of Munich (TUM) / TUM University Hospital in the Department of Diagnostic and Interventional Radiology, within the AI-Assisted Healthcare Lab and the EU Horizon Europe project TWIN-X.

The project focuses on foundation models and digital patient twins for precision medicine, especially in oncology and cardiovascular medicine. The successful candidate will work with large-scale multimodal clinical data, including radiological imaging, digital pathology, genomics, laboratory values, clinical notes and reports, and longitudinal patient trajectories.

Research directions mentioned include heterogeneous and asynchronous clinical data modelling, cross-attention models, mixture-of-experts systems, temporal transformers, JEPA-style architectures, self-supervised learning, contrastive learning, masked modelling, and generative pretraining. The role is strongly research-oriented and encourages candidates to contribute their own ideas.

Funding and resources are strong: the position is full-time TV-L E13 for 48 months, with access to two NVIDIA B300 servers plus additional H100/H200 GPU servers, large-scale storage, conference travel support, and opportunities for short research stays at partner institutions in Europe.

Applicants should have an excellent master’s degree in computer science, mathematics, physics, engineering, medical informatics, biomedical engineering, or a related field; strong quantitative preparation; strong Python skills; experience with deep learning frameworks 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.

To apply, email the required documents to the listed supervisors. Complete Bachelor’s and Master’s transcripts are mandatory, along with a cover letter, CV, and degree certificates. Optional materials include a publication list, code portfolio/GitHub profile, and academic references.

Location: Munich, Germany. Project: TWIN-X: Digital Twins with Generative AI for Explainable Precision Medicine.

Funding details

Full funding including tuition fees and living expenses is available for this position. The scholarship covers all educational costs and provides a monthly stipend.

How to apply

Please submit your application including a cover letter, CV, academic transcripts, and contact information for two references. Applications should be sent via the online portal before the deadline.

More information can be found here

Ask ApplyKite AI

Start chatting
Can you summarize this position?
What qualifications are required for this position?
How should I prepare my application?