Artificial Intelligence

(MCRC Non-Clinical) Personalising Prostate Cancer Radiotherapy Using Imaging and Genomic Biomarkers

The University of Manchester

Not stated

Location
Manchester, United Kingdom
Funding
Competition Funded PhD Project (Students Worldwide)
Application deadline
23 November 2026

About the project

About the Project Radiotherapy is an effective treatment for prostate cancer, but men vary widely in their susceptibility to radiation-induced side effects. While some experience significant rectal and bladder toxicity, others tolerate similar radiation doses well with minimal or no side effects. This variation suggests that individual differences in normal tissue biology influence response to radiotherapy. Emerging evidence indicates that some men may be able to safely receive lower doses to non-tumour prostate tissue while maintaining effective tumour control. Treatment de-intensification could reduce radiation exposure to surrounding normal tissues and potentially minimise treatment-related side effects, preserving quality of life. However, successful implementation requires accurate identification of men most likely to benefit. Current treatment selection relies largely on clinical risk and doesn’t capture individual differences in normal tissue susceptibility. This project will investigate whether pre-treatment multiparametric MRI can identify spatially varying biological characteristics of normal tissue that influence radiation-induced toxicity. Building on our group's expertise in quantitative imaging and spatial radiotherapy dose analysis, the student will develop spatial MRI-derived biomarkers of rectal and bladder tissue phenotype using quantitative MRI measures and radiomic features. These imaging biomarkers will be integrated with three-dimensional radiotherapy dose distributions to determine whether normal tissue phenotype modifies local dose-toxicity relationships. The project will also investigate inherited genetic markers of radiosensitivity and their contribution to individual toxicity risk. Using multi-centre cohorts with linked clinical, imaging, radiotherapy, genomic, and toxicity data, the student will develop and validate predictive models integrating imaging-derived tissue phenotype, spatial dose, clinical factors, and inherited radiosensitivity. The project will build a biologically informed framework for predicting radiotherapy-induced toxicity and identifying men who are suitable for treatment de-intensification. Ultimately, this research aims to support more personalised prostate cancer radiotherapy by identifying patents who can safely receive less radiation while maintaining effective tumour control. Eligibility You must hold, or about to obtain, a minimum Upper Second Class UK honours degree, or the equivalent qualifications gained outside the UK, in a relevant discipline. A related master’s degree would be an advantage International applicants (including EU nationals) must ensure they meet the academic eligibility criteria (including English language) before contacting potential supervisors to express an interest in their project. Eligibility information can be found on the University's Country Specific information page. Before you Apply Applicants must make direct contact with preferred supervisors before applying. It is your responsibility to make arrangements to meet with potential supervisors, prior to submitting a formal online application. How to Apply Apply directly via this link: https://tinyurl.com/577zjazd or on the online application portal, select MCRC PhD Programme as the programme of study. You may only apply for one project within this scheme. Please ensure that your application includes all required supporting documents: Curriculum Vitae (CV) Supporting Statement Academic Certificates and Transcripts Incomplete or late applications will not be considered. Further details are available on our website: CRUK Manchester Centre PhD Training Scheme | Biology, Medicine and Health | University of Manchester Application Timeline Applications open: Monday, 5 October 2026 Application deadline: Monday, 23 November 2026 Interview date: Week commencing 11 January 2027 Start date: September 2027 Equality, diversity and inclusion are central to the University’s activities. The full statement can be found here: https://www.bmh.manchester.ac.uk/study/research/getting-started/equality-diversity-inclusion/

Research areas

Artificial IntelligenceComputational PhysicsMachine LearningMedical PhysicsCancer BiologyData ScienceStatisticsBiophysics