AI models for histopathological image analysis for cancer grading and progression assessment

Applications are invited for this fully funded PhD position on AI models for histopathological image analysis for cancer grading and progression assessment.

The assessment of pathological cancer regression after preoperative chemotherapy is mostly based on the assessment of tumour morphological features, such as the proportion of cancer cells in relation to the total tumour region, as well as biologically relevant histology features, such the tumour invasion front. Currently, this histopathological evaluation is performed by expert pathologists through visual assessment of the tumour microscopic slides. This is often time-consuming, expensive and may be unacceptably inconsistent and imprecise. This project aims at developing an artificial intelligence (AI) system that enables automatic, precise, objective and reproducible assessment of tumour regression and precise characterisation of the tumour invasion front based on the digital scans of resected tumour tissue slides, by integrating beyond the state-of-the-art, specifically designed computer vision, image processing and deep learning schemes.

How to apply
The studentship will be based in the School of Electronic Engineering and Computer Science (EECS) www.eecs.qmul.ac.uk at Queen Mary University of London, in the Multimedia and Vision Research Group. The project undertaken under this studentship is expected to fit into the wider research programme of the group, which has widespread recognition for its research in image processing and computer vision areas.

This studentship, funded by the School of Electronic Engineering and Computer Science, is for 3 years and will cover student fees and a tax-free stipend starting at £16777 per annum. Candidates should have a first class honours degree or equivalent, or a strong Masters Degree, in computer science, mathematics, or electronic engineering. Enquiries should be directed to [Email Address Removed].

To apply please follow the on-line process (see www.qmul.ac.uk/postgraduate/apply ) by selecting “Electronic Engineering ” in the “A-Z list of research opportunities” and following the instructions on the right hand side of the web page.

Please note that instead of the 'Research Proposal' we request a 'Statement of Research Interests'. Your Statement of Research Interest should answer two questions: (i) Why are you interested in the proposed area? (ii) What is your experience in the proposed area? Your statement should be brief: no more than 500 words or one side of A4 paper. Mark clearly the statement with Your Name and the title “AI models for histopathological image analysis for cancer grading and progression assessment”. In addition we would also like you to send a sample of your written work. This might be a chapter of your final year dissertation, or a published conference or journal paper. More details can be found at: www.eecs.qmul.ac.uk/phd/apply.php.