Division: Imaging Science and Technology
Deadline for applications: 22nd March 2021
Glioblastoma multiforme (GBM) is associated with a median survival of just over one year and is the most common and aggressive malignant brain tumour. Brain biopsy is the gold standard for classification of histology and molecular characteristics but complicated by tumour heterogeneity. Routinely acquired NHS brain MR imaging allows diagnosis and tumour segmentation for surgery and radiotherapy planning. Quantitative analysis of tumour volume image characteristics, termed Texture Analysis (TA), can allow prediction of patient survival, glioma grade and molecular status, but is not routinely done.
The aims of this PhD studentship are: a) to develop new multiscale computer code for TA incorporating the best existing methods and b) combine it with machine learning to determine accuracy of prediction of patient survival and tumour characteristics. Multiscale tumour growth models will be further developed and fitted to NHS scan data, to c) determine whether this added longitudinal information enhances the accuracy of individual patient predictions.
The project will suit a student with a strong mathematics and/or computer science background interested in applying their expertise to medical research. Training will be provided in the clinical context of this translational study, neuroimaging, machine learning and computational modelling. The student will be encouraged to present their work at Research in Progress meetings and later at national and international meetings and will be registered with a Thesis Monitoring Committee in the Medical School.
Applicants to complete the Application form and email to [Email Address Removed] along with a CV and 2 academic references by Monday 22nd March 2021.
First class honours degree, and/or a Masters degree in a relevant discipline. (Non-clinical applicants)
MBChB (clinical applicants)
English language requirements
IELTS minimum overall score of 6.5
Reading 5.5, Listening 5.5, Speaking 5.5 Writing 6.0