Radiotherapy is a very effective method of tumour control but some patients suffer from side effects that affect their quality-of-life. We have been working to find predictors of radiotherapy toxicity, including genetics and clinical factors, through the REQUITE project. An important factor in the variability of side effects is the radiation dose distribution, particularly to the organs and tissues that are around the tumour target volume.
The aim of the project is to use artificial intelligence approaches to analyse thousands of CT scans from radiotherapy patients to identify image features that can predict side effects.
The project is a collaboration between a team at the University of Leicester that works on radiotherapy side effects (Talbot & Rattay), a computer scientist who specialises in AI analysis of medical images (Zare) and a Belfast-based company that develops AI-based services for medicine (Axial3D).
The studentship will be based in Leicester, but the student will spend three months working at Axial3D, therefore gaining experience in both academic and commercial environments. The project would suit a student with experience in computer science, mathematics or medical physics.
Entry requirements: You must hold (or be about to obtain) a First or an Upper Second Class UK undergraduate degree or an equivalent degree from a recognised EU institution, in an area relevant to the projects you are applying for.
Qualifications (or a combination of qualifications and experience) which demonstrate equivalent ability and attainment will also be considered.
For example, a less than sufficient first degree may be enhanced to meet the requirements by the acquisition of a Distinction at Masters level or significant research experience gained from employment).
Informal enquiries: If you have any questions or would like to find out more about IMPACT, please get in touch. Email us at [email protected]