Magnetic Resonance Imaging (MRI) is central to modern diagnostics, offering rich contrast in soft tissues and extensive clinical utility. However, current MRI systems suffer from long scan times (30–40 min per patient) due to weak and spatially complex signals and the need for manual configuration of pulse sequences. The Computer Engineering (CE) section of the Quantum & Computer Engineering (QCE) department seeks a PhD candidate to develop AI‑based predictive intelligence for MRI scanning. The candidate will work on the following:
- Design a foundation model (FM) capable of generalizing across patient anatomies, pathologies, and coil arrangements to infer optimal sensor settings from partial data.
- Develop a system architecture and training strategy enabling the FM to learn from heterogeneous MRI data in terms of data source purpose and physical location in the scanner.
- Devise efficient techniques to turn partial MRI measurements into meaningful input for predicting optimal sensor phase configurations and feedback control.
- Investigate pathways to integrate domain knowledge about MRI physics into the learning process to guide or constrain the model’s predictions.
- Develop solutions to address integration issues within existing medical procedures.
The PhD position is part of SAMURAI, a national project in collaboration with Philips Medical Systems.
Responsibilities- Design forward‑looking AI models and validate their performance on real‑world MRI data.
- Collaborate with clinical and engineering teams to define use‑case requirements and gather data.
- Implement scalable software pipelines for data preprocessing, model training, and deployment.
- Present findings at internal and external meetings, writing technical reports and publications.
- Completed a relevant MSc in Electrical Engineering, Computer Engineering, Computer Science, or a related field.
- Good understanding of computer architecture.
- Basic understanding of MRI algorithms is a plus.
- Strong background in AI and its practical implementations.
- Ability to work in a team, take initiatives, and communicate effectively.
Doctoral candidates will be offered a 4‑year period of employment with an initial 1.5‑year contract followed by a continuation contract for the remaining 2.5 years, contingent on performance. The appointment begins with a 1.5‑year probationary period.
Salary is based on the Dutch Universities collective labor agreement, ranging from €3 059 to €3 881 gross per month (full‑time, 38 h), plus 8 % holiday allowance and an end‑of‑year bonus of 8.3 %.
PhD candidates will be enrolled in the TU Delft Graduate School, gaining access to a strong mentorship and research environment.
Application procedurePlease submit CV, a one‑page motivational letter tailored to this position, and supporting documents demonstrating writing and scientific skills. Applications must be received by 17 January 2026 via the application button. Online applications will be processed; email or postal applications are not accepted.
Contact Prof. Dr. Ir. Georgi Gaydadjiev for more information.
#J-18808-Ljbffr€3059 - €3881 monthly