Computational imaging for democratisation of MRI in medicine

The Biomedical and Astronomical Signal Processing (BASP) laboratory at Heriot-Watt University Edinburgh (HWU), headed by Professor Yves Wiaux is recruiting a PhD student for research on computational imaging for magnetic resonance imaging (MRI) in low-resource settings.

The BASP laboratory is developing cutting-edge research on all aspects of computational imaging, from theory and algorithms to a applications across astronomy and medicine. Dr Wiaux is a Professor in the School of Engineering and Physical Sciences at HWU. He is also Honorary fellow at the School of Informatics of the University of Edinburgh (UoE), and Academic Guest at the Signal Processing Laboratories of the Ecole Polytechnique Fédérale de Lausanne (EPFL).

The position is open in the context of large research projects funded by the UK Research Councils, aiming to develop a new generation of image reconstruction and analysis algorithms at the interface of deep learning, optimisation, and Bayesian sampling. The algorithms are intended to deliver simultaneously high-quality imaging, to include calibration and uncertainty quantification functionalities, and to enable scalability to large image sizes and data volumes. They will be designed, implemented, and validated for various applications in astronomy and medicine.

The PhD project will focus on the development of image reconstruction algorithms for low-field MRI. The relative low cost and low footprint of scanners operating at low magnetic field make them much more affordable than their cutting-edge high-field counterparts. However, the resulting low quality of the data acquired typically implies low-quality images. By enabling diagnostic-quality imaging from the low-quality data of low-cost scanners, the project will contribute to democratising access to MRI across the world, in regions where high-field scanners are not affordable, in particular Low and Middle income countries (LMICs). In this context, the project will focus on: (i) the development of image reconstruction algorithms at the interface of deep learning and optimisation, including image estimation and uncertainty quantification functionalities; (ii) their specialisation to low-field MRI; (iii) their validation on case studies for neuroimaging, from data acquired by a variety ofexisting low-field scanners, as well as experimental portable ultra-low-field scanners.

The project is supported by a unique team of international partners bringing unique expertise in low-field MRI, among which the Lausanne University Hospital (CHUV, Dr R. van Heeswijk), the Leiden University Medical Center (LUMC, Prof. A. Webb), and the Ecole Polytechnique Fédérale de Lausanne (EPFL, Prof. JP. Thiran).

We are looking for outstanding candidates with a first Class Master’s Degree (or equivalent) in electrical engineering, applied mathematics, physics, computer science, or a related discipline. The student will be fully integrated into BASP under the supervision of Prof. Wiaux, with co-supervision by the relevant collaborators from the participating institutions.

The scholarship is fully-funded for 3.5 years, and open to international students. The start date is flexible from September 2025. Expressions of interest and full applications (single PDF including a motivation letter, full transcript of record, CV, and names of 2 references) should be sent by email to Prof. Wiaux ([email protected]). Please apply at your earliest convenience. Applications screening will start in October 2025 and continue until the position is filled.