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Self-Supervised Machine Learning as a Tool to Measure Cancer Prognosis

   College of Medicine, Veterinary and Life Sciences

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  Dr R Insall, Dr Ke Yuan  No more applications being accepted  Funded PhD Project (UK Students Only)

Glasgow United Kingdom Cancer Biology

About the Project


Prof Robert Insall

Dr Ke Yuan

PhD Project Summary:

This project will use a recently-described deep learning technique – self-supervised contrastive learning – to identify patterns in colon cancer and in precancerous polyps, which will enable pathologists to give patients a more accurate prognosis. A large dataset of pathology images is available. The student will create new contrastive learning networks, and train them to identify key features that discriminate different samples. They will then test which of these features lead to poor patient outcomes. The student will be trained in both cancer pathology and deep learning techniques, equipping them with a toolset that is both medically useful and in very high demand.

Funding Notes

The studentship provides funding for tuition fees, a stipend and laboratory expenses for Home (UK) applicants only.
The MVLS/EPSRC grant provides tuition fees and stipend of at least £15,285 (UKRI rate 2020/21).
Please view application information here:
Once you have all the required application documentation, please apply here:
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