PhD Position on Predictive Modeling of Magnetic Resonance Imaging

PhD Position on Predictive Modeling of Magnetic Resonance Imaging

Job Description

Magnetic Resonance Imaging (MRI) is central to modern diagnostics, offering rich contrast in soft tissues and extensive clinical utility. However, a key limitation remains: the long scan times, often 30–40 minutes per patient, due to the weak and spatially complex nature of MRI signals. Each MRI examination involves multiple pulse sequences, with signal acquisition being sensitive to coil placement, sensor geometry, B0/B1 inhomogeneities, patient motion, and more. Today, these parameters are either manually configured, heuristically optimized, or compensated post hoc using multi-level calibration scans or corrections, which introduces further latency. Crucially, current MRI systems lack any form of predictive intelligence that could inform optimal configuration ahead of, or during scanning.

The Computer Engineering (CE) section of the Quantum & Computer Engineering (QCE) department is looking for a highly motivated PhD candidate who is eager to work on AI-based solutions for predictive intelligence for MRI scanning. The PhD position is part of the SAMURAI, a national project in collaboration with Philips Medical Systems. You will be part of a diverse and passionate research team of academic staff, PhD candidates and Postdoctoral researchers in the Computer Engineering group.

Key Responsibilities

• Design an efficient foundation model (FM) for generalization across patient anatomies, pathologies, and coil arrangements to infer optimal sensor settings from partial data.
• Develop system architecture and training strategy to enable the FM to learn from heterogeneous MRI data in terms of data source purpose and physical location in the scanner.
• Develop efficient techniques to turn partial MRI measurements into meaningful input for predicting optimal sensor phase configurations and feedback control.
• Identify pathways towards the integration of domain knowledge about MRI physics into the learning process to guide or constrain the model’s predictions.
• Develop solutions to address the issues related to integration in existing medical procedures.

Job Requirements

• Completed a relevant MSc degree in Electrical Engineering, Computer Engineering, Computer Science or any other related field relevant to the research.
• Good understanding of computer architecture.
• Basic understanding of MRI algorithms is a plus.
• Understanding of AI and its practical implementations.
• The ability to work in a team and take initiatives.

TU Delft (Delft University of Technology)

Delft University of Technology is built on strong foundations. As creators of the world-famous Dutch waterworks and pioneers in biotech, TU Delft is a top international university combining science, engineering and design. It delivers world class results in education, research and innovation to address challenges in the areas of energy, climate, mobility, health and digital society. For generations, our engineers have proven to be entrepreneurial problem-solvers, both in business and in a social context.

Faculty of Electrical Engineering, Mathematics and Computer Science

The Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) brings together three scientific disciplines. Combined, they reinforce each other and are the driving force behind the technology we all use in our daily lives. Technology such as the electricity grid, which our faculty is helping to make completely sustainable and future-proof. At the same time, we are developing the chips and sensors of the future, whilst also setting the foundations for the software technologies to run on this new generation of equipment – which of course includes AI. Meanwhile we are pushing the limits of applied mathematics, for example mapping out disease processes using single cell data, and using mathematics to simulate gigantic ash plumes after a volcanic eruption. In other words: there is plenty of room at the faculty for ground-breaking research. We educate innovative engineers and have excellent labs and facilities that underline our strong international position. In total, more than 1000 employees and 4,000 students work and study in this innovative environment.

Conditions of Employment

Doctoral candidates will be offered a 4-year period of employment in principle, but in the form of 2 employment contracts. An initial 1.5 year contract with an official go/no go progress assessment within 15 months. Followed by an additional contract for the remaining 2.5 years assuming everything goes well and performance requirements are met.

Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities, increasing from €3059 - €3881 gross per month, from the first year to the fourth year based on a fulltime contract (38 hours), plus 8% holiday allowance and an end-of-year bonus of 8.3%.

As a PhD candidate you will be enrolled in the TU Delft Graduate School. The TU Delft Graduate School provides an inspiring research environment with an excellent team of supervisors, academic staff and a mentor. The Doctoral Education Programme is aimed at developing your transferable, discipline-related and research skills.

The TU Delft offers a customisable compensation package, discounts on health insurance, and a monthly work costs contribution. Flexible work schedules can be arranged.

Additional Information

If you would like more information about this vacancy or the selection procedure, please contact Prof. Dr. Ir. Georgi Gaydadjiev, via g.n.gaydadjiev@tudelft.nl or Dr. Ir. Motta Taouil, m.taouil@tudelft.nl.