AI-driven signal and imaging analysis in cancer diagnosis

Cancer remains one of the leading causes of death worldwide. Increasing evidence indicates that how cancers develop and respond to treatments is linked to each patient’s unique tumour microenvironment.  A deeper understanding of the roles the tumour microenvironment plays in cancer development could lead to improved early diagnosis and the development of more precisely-targeted and effective therapies.

The aim of this PhD project is to leverage cutting-edge Raman spectroscopy, combined with AI-driven image analysis and bioinformatics tools, to map molecular information in clinical tissue samples. This approach will provide a holistic view of the cancer cell biology, offering the potential to identify biomarkers for early diagnosis and to stratify patients for tailored treatment regimens. The project is a part of international collaboration, and the student will join a dynamic, interdisciplinary team, working alongside world-class research groups at the University of Oxford, National Physical Laboratory, London and MD Anderson Cancer Centre, Texas. 

We are seeking a motivated candidate to apply for a James Watt School of Engineering Doctoral studentship (and/or the Dunlop Scholarship for Women) to join an internationally leading research group. The successful applicant will be part of the Advanced Diagnosis Group, based in state-of-the-art laboratories within the Advanced Research Centre at the University of Glasgow. Applications are welcome from highly motivated candidates with strong backgrounds in the following or related disciplines such as computer science, engineering, chemistry, physics or similar. 

Candidates will ideally hold a master’s level qualification and an undergraduate degree in relevant area.

Informal enquires and full application (curriculum vitae, cover letter and contact details of two referees) to Prof Huabing Yin