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 inteligence for MRI scanning. The candidate will work on the following:

• Design of 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;
• Identifying pathways towards the integration of domain knowledge about MRI physics into the learning process to guide or constrain the model’s predictions;
• Developing solutions to address the issues related to integration in existing medical proceudres.

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. Curious to learn more about the project, and perhaps our group? Feel free to browse our webpages:

• About our department: QCE department.
• About our group: Computer Engineering Lab.

Job requirements

For this position, an ideal candidate should have:

• 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.

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.

Will you need to relocate to the Netherlands for this job? TU Delft is committed to make your move as smooth as possible! The HR unit, Coming to Delft Service, offers information on their website to help you prepare your relocation. In addition, Coming to Delft Service organises events to help you settle in the Netherlands, and expand your (social) network in Delft. A Dual Career Programme is available, to support your accompanying partner with their job search in the Netherlands.

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.

Application procedure
Are you interested in this vacancy? Please apply no later than 17 January 2026 via the application button and upload the following documents:

• CV
• 1 page Motivational letter tailored to the position you are applying for

• (part of your) papers that you have written, in which you demonstrate your writing (and scientific) skills.

You can address your application to Prof. Dr. Ir. Georgi Gaydadjiev.

Doing a PhD at TU Delft requires English proficiency at a certain level to ensure that the candidate is able to communicate and interact well, participate in English-taught Doctoral Education courses, and write scientific articles and a final thesis. For more details please check the Graduate Schools Admission Requirements.

Please note:

• You can apply online. We will not process applications sent by email and/or post.
• As part of knowledge security, TU Delft conducts a risk assessment during the recruitment of personnel. We do this, among other things, to prevent the unwanted transfer of sensitive knowledge and technology. The assessment is based on information provided by the candidates themselves, such as their motivation letter and CV, and takes place at the final stages of the selection process. When the outcome of the assessment is negative, the candidate will be informed. The processing of personal data in the context of the risk assessment is carried out on the legal basis of the GDPR: performing a public task in the public interest. You can find more information about this assessment on our website about knowledge security.
• Please do not contact us for unsolicited services.