PhD Studentship – Predicting Infiltrative Glioblastoma Progression using Advanced Magnetic Resonance Imaging Methods
University of Nottingham
Nottingham, England, United Kingdom
General Description
The University of Nottingham is inviting applications for a fully‑funded PhD Studentship focused on developing innovative imaging analysis and predictive modelling approaches to understand and forecast the progression of infiltrative glioblastoma using advanced magnetic resonance imaging (MRI) methods. Glioblastoma (GBM) is the most common and aggressive adult brain tumour, with recurrence driven by infiltrative tumour cells at the tumour margin. This multi‑disciplinary project will involve using cutting‑edge anatomical and physiometabolic MRI techniques, including arterial spin labelling perfusion, neurite orientation dispersion and density imaging (NODDI), and chemical exchange saturation transfer, to explore at‑risk sites for early relapse before clinical progression is visible. The research will also focus on statistical and AI‑driven strategies to develop novel biomarkers that link imaging features to underlying phenometabolic signatures from matched surgical tissue samples. The opportunity sits within the new Brain Tumour Research Centre of Excellence at Nottingham, spanning multiple faculties and offering a collaborative translational research environment with international partners and access to state‑of‑the‑art imaging infrastructure.
Eligibility Criteria
Applicants should hold (or be close to completion of) a strong undergraduate degree in a relevant subject such as Biomedical Sciences, Biomedical/Information Engineering, Computer Science, Analytical Bioscience, Physics, or related disciplines. Prior experience with medical imaging, especially MRI, and computational analysis (e.g., Python/R/MATLAB, machine learning or bioinformatics) is highly desirable.
Required expertise/skills
Background in MRI science, image analysis or related quantitative methods.
Demonstrated ability in computational data analysis and modelling (e.g., Python, R, or MATLAB).
Capacity for interdisciplinary research combining imaging, biological data and statistical modelling.
Salary details
This 4‑year PhD Studentship includes tuition fees at the UK Home student rate and an annual stipend at current UK Research & Innovation (UKRI) rates for doctoral students.
Application Deadline
1 April 2026 (applications will be considered on a rolling basis).