Machine Learning approaches to improve the treatment of Prostate Cancer

Prostate Cancer UK (PCUK) Funded 4 year PhD Studentship

Prostate Cancer is a highly heterogeneous disease with complex characteristics of progression. New therapies have produced some clinical successes, but a subset of patients progress to incurable disease and it is not yet possible to predict which patients will respond best to which treatments. There is an urgent need to develop better biomarkers with which to stratify patient populations and to personalise therapies in order improve clinical outcome.

This studentship, which is open to exceptional candidates from a computational background, will use techniques from machine learning to develop new models of prostate cancer gene expression. The successful applicant will have access to a large High Performance Computing (HPC) facility on site, and will join a highly interdisciplinary research programme that integrates computer science and machine learning, with basic- and clinical-science.

The project will focus on the role played by noncoding RNAs, a newly discovered set of genes that often regulate other processes within our cells. It will use computational techniques to study the changes in gene expression that accompany drug treatments, and then use these insights to develop novel biomarkers predictive of patient response.

No prior knowledge of cancer biology is required; applicants from artificial intelligence, mathematics, physics or other numerical disciplines are particularly encouraged to apply.

To make an application please click the ‘Apply Online’ button.