The candidate will have, or expect to obtain, a 1st or 2:1 honours degree in physics or a related subject. A knowledge of optics, photonics, radiation physics and or signal processing and image analysis techniques would be an advantage.
The ideal candidate will have experience with practical instrumentation and experiments. they will feel comfortable using numerical techniques for modelling and data processing.
Experience working in industry or in the medical devices industry would be an advantage.
Please note that the successful candidate for this project will spend the majority of their time based at Lightpoint Medical in Chesham.
The project is fully funded for four years including fees and a stipend for eligible students. successful applicants will be part of a small yearly cohort that will meet for networking, technical and MBA courses as well as professional skills workshops.
This industry led project involves the application of signal processing and optical engineering to advance the state of the art in medical imaging for cancer surgery. Cancer surgery is often unsuccessful, resulting in the need for multiple operations or increasing the need for additional drug treatment or radiotherapy. For example, approximately 25% of patients undergoing surgery for prostate cancer will have a positive surgical margin which is an indicator of incomplete cancer removal. Surgery is unsuccessful so often because surgeons lack a tool to detect cancerous tissue in real time during surgery.
This pressing need can be met through the development of intra-operative technology for detecting radiopharmaceutical tracers which are currently used for pre-operative PET and SPECT scans. These novel techniques face engineering challenges due to the time, space and activity concentration constraints of the application as well as physics challenges due to the need to collect and interpret complex signals due to radiation absorption, scattering effects and the presence of interferences. This Eng-D project will build both a theoretical and practical understanding of two contrasting approaches; in-vivo detection of cancer during laparoscopic surgery and detection of cancerous margins on ex-vivo samples. This will involve Monte Carlo simulations of the radiation physics (e.g. GEANT4), investigating sources of interference in practice and developing signal processing and visualisation techniques (e.g. MATLAB/Python). Promising advances will be further investigated through experiment, prototyping and using real data and images from medical instruments. This work will be done in close collaboration with industry, with the student being placed at Lightpoint Medical.