PhD Studentship: Predicting Infiltrative Glioblastoma Progression using Advanced Magnetic Resonance Imaging Methods

Glioblastoma (GBM) is the most common and lethal adult brain tumour, with relapse driven by infiltrative tumour cells that escape surgical resection and resist therapy. These residual GBM cells at the tumour margin represent a key target for earlier and more effective therapeutic intervention.

This PhD project will develop advanced MRI analysis methods and imaging-driven predictive models focusing on the glioblastoma infiltrative margin. This involves use of anatomical and physiometabolic imaging methods, including arterial spin labelling perfusion, neurite orientation dispersion and density imaging (NODDI), and chemical exchange saturation transfer. By combining multiple modalities and parameters, we aim to identify at risk sites for GBM relapse at the earliest opportunity, before progression becomes apparent clinically.

We will develop cancer biomarkers through statistical models, including AI driven strategies, to predict highly aggressive tissue molecular signatures for mapping future GBM relapse, linking imaging features to phenometabolic signatures from tissue samples taken during surgery and matched to the imaging.

The project is part of the imaging theme for the new Nottingham Brain Tumour Research Centre of Excellence. This is a unique opportunity to work on advanced image analysis and image-driven modelling as part of a wider multi-disciplinary programme that includes mathematical modelling, cancer metabolomics and novel physiological MRI technique development within a translational research environment bridging analytical bioscience and neuro-oncology.

Research Environment

The successful applicant for a 4-year PhD studentship will join the Brain Tumour Research Centre of Excellence (5-year programme grant) at the University of Nottingham — a cross-Faculty, multidisciplinary partnership spanning the Schools of Medicine, Life Sciences and Pharmacy. The Centre brings together experts in molecular neuro-oncology, biomedical imaging, analytical bioscience, mathematical modelling, and polymer therapeutics, alongside international collaborators at Erasmus University Rotterdam (Netherlands), the Mayo Clinic Arizona (USA) and the University of Freiburg (Germany).
This project will be based in Precision Imaging (School of Medicine), which houses world-class infrastructure including a 3T Philips Elition intraoperative MRI suite (at Queens Medical Centre) and is part of the Sir Peter Mansfield Imaging Centre at the University of Nottingham which has a recently upgraded 7T MRI and will open the UK’s National Ultra High Field (11.7T) MRI facility within the direction of the project.

Eligibility

Strong undergraduate degree in a relevant subject – Biomedical Sciences, Biomedical/Information Engineering, Computer Science, Analytical Bioscience, Physics or related disciplines.

Prior experience with medical imaging, particularly MRI, medical physics or computational data analysis (Python/R/MATLAB, machine learning, or bioinformatics) is highly desirable.

Interested candidates should send a CV to michael.chappell@nottingham.ac.uk.

Deadline: 1^st April 2026 for a September 2026 start.

Funding notes: This 4-year PhD studentship will include tuition fees for home students and an annual stipend equivalent to current UKRI rates.

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