PhD in Physics-Informed Generative AI for Dynamic Cardiac MRI
Develop trustworthy generative AI methods to enable safer, low-dose cardiac MRI examinations.
Best for:Best for graduate students in engineering or computer science with a background in deep learning, PyTorch, and a strong interest in medical imaging.
Overview
Eindhoven University of Technology and the Technical University of Munich invite applications for a four-year PhD position within the PRIMA-CMR project, part of the EuroTech Universities Alliance. The research focuses on developing reliable generative artificial intelligence models to recover diagnostic information from low-dose cardiac MRI scans while quantifying uncertainty for clinical validation. The successful candidate will be based primarily in the Medical Image Analysis group at Eindhoven University of Technology and spend six months at the Technical University of Munich. The candidate is expected to conduct independent research, publish findings in leading venues, and contribute to teaching tasks.
What you'll do
- Design and implement novel generative AI architectures for reconstructing low-dose cardiac MRI images.
- Integrate physics-based modeling and uncertainty quantification techniques into machine learning pipelines.
- Validate developed algorithms on real clinical datasets in collaboration with international clinical partners.
- Spend a six-month research visit at the Technical University of Munich within the research group of Professor Julia Schnabel.
- Disseminate research outcomes through peer-reviewed publications and conference presentations.
- Contribute to teaching and student coaching activities up to 15 percent of annual working time.
- Participate in interdisciplinary network activities across the EuroTech Universities Alliance.
Requirements
Degree required: Master’s degree in Biomedical Engineering, Computer Science, Electrical Engineering, Applied Physics, Applied Mathematics, or a related field
Degree offered: PhD
Language: English; fluent in spoken and written English at C1 level
Instruction: English
- Solid academic background in deep learning and interest in generative modeling
- Proficiency in Python programming language
- Hands-on experience with deep learning frameworks such as PyTorch
- Strong analytical thinking and problem-solving capabilities
- Ability to work effectively within an international and interdisciplinary team
- Must hold an eligible university master's degree prior to commencement
- Willingness to complete a mandatory six-month research stay in Munich, Germany
Funding & terms
How to apply
Deadline: 2026-11-21 (Europe/Amsterdam)
Applicants must submit their complete application package through the official online recruitment portal before the stated deadline. Ensure all required documentation including academic transcripts and motivation letters are attached in accordance with institutional guidelines.
- CV
- Cover letter
- Master's degree transcripts
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