Summary
Eindhoven University of Technology (TU/e) is offering a PhD position for the PRIMA-CMR project, a collaboration with the Technical University of Munich (TUM). The research focuses on developing trustworthy generative AI to make cardiac MRI safer by significantly reducing the need for gadolinium-based contrast agents. This position involves combining MRI physics with deep learning and includes a six-month research stay in Munich.
Position Overview
| Designation | PhD Candidate |
| Institution | Eindhoven University of Technology (TU/e) |
| Department | Biomedical Engineering |
| Research Group | Medical Image Analysis |
| Location | Eindhoven, Netherlands (with 6 months at TUM, Germany) |
| Salary | €3,204 to €4,051 gross per month |
| Duration | 4 years (Full-time) |
| Application Deadline | November 21, 2026 |
Research Area
The research focuses on Medical Image Analysis and Generative Artificial Intelligence. Specifically, the PhD candidate will develop physics-informed AI models to recover diagnostic information from low-dose cardiac MRI. The project aims to integrate MR imaging physics, clinical data, and uncertainty quantification to ensure the AI outputs are reliable and clinically trustworthy.
Scholarship Description
This PhD position is part of the EuroTech Universities Alliance programme. Benefits include:
- A full-time employment contract for four years.
- A gross monthly salary starting at €3,204 in the first year, rising to €4,051 in the fourth year.
- An 8% holiday allowance and an 8.3% year-end bonus.
- A six-month research exchange at the Technical University of Munich (TUM) under the supervision of Prof. Julia Schnabel.
- Generous leave options (29 to 41 days per year).
- Access to high-quality training programs and a vibrant international research ecosystem.
- Commuting, home-working, and internet allowances.
Eligibility/Qualification
Interested candidates should meet the following criteria:
- A Master’s degree in Biomedical Engineering, Computer Science, Electrical Engineering, Applied Physics, Applied Mathematics, or a related field.
- A strong background in deep learning, particularly generative models.
- Proficiency in Python and deep learning frameworks like PyTorch.
- Knowledge of MRI physics, physics-based modeling, or inverse problems is highly desirable.
- Excellent analytical thinking and problem-solving skills.
- Willingness to travel and work in an international, interdisciplinary team.
- Fluency in spoken and written English (C1 level).
How to Apply
Applications must be submitted through the TU/e online recruitment portal. Emailed applications will not be accepted. The application package should include:
- Cover Letter: Detailing your motivation and specific qualifications for this research.
- Curriculum Vitae: Including a list of publications and contact details for three references.
- MSc Thesis Description: A brief summary of your thesis topic, methods, and contributions.
- Transcripts: A list of Bachelor’s and Master’s courses with grades.
Last Date for Apply
The application deadline is November 21, 2026. However, the vacancy may remain open until a suitable candidate is found.
Apply Link
Interested candidates can apply directly through the official TU/e vacancy page: Apply for PhD in Physics-informed Generative AI
