DPhil Studentship in Clinical Mass Spectrometry and Machine Learning for Brain Tumour Characterisation University of Oxford in United Kingdom

The University of Oxford’s Department of Chemistry invites applications for a DPhil studentship in clinical mass spectrometry and machine learning, supervised by Professor Claire Vallance. This fully funded opportunity, sponsored by the Doogood Foundation, is available from October 2026 and offers course fees at the Home rate plus a stipend of at least £20,780 per annum for four years. The project is based in the Chemistry Research Laboratory (CRL) and involves close collaboration with consultant pathologist Olaf Ansorge and consultant neurosurgeon Puneet Plaha at Oxford’s John Radcliffe Hospital.

The research focuses on the application of atmospheric pressure and imaging mass spectrometry to clinical medicine, specifically the characterisation of brain tumours. Building on a recent pilot study, the project aims to use atmospheric pressure ionisation mass spectrometry coupled with machine learning to differentiate between brain tumours and normal tissue. The next phase will investigate the infiltration zone at the boundary between tumour and healthy tissue, with the goal of developing improved methods for defining surgical boundaries during tumour resection. Additional related research avenues may also be explored, offering a broad scope for scientific inquiry.

The Vallance group’s research integrates experimental work and advanced data analysis, leveraging machine learning and statistical techniques. Candidates will have the opportunity to work at the intersection of chemistry, medical science, and computational analysis, spending significant time both in the laboratory and at the hospital. The group is committed to diversity, equality, and inclusion, and holds the Athena SWAN Silver Award.

Applicants should possess a first-class or strong upper second-class undergraduate degree in Chemistry, medical sciences, or a related subject. While prior experience in mass spectrometry, statistical data analysis, machine learning, or scientific programming is advantageous, it is not essential. The ideal candidate will demonstrate a strong commitment to research, the ability to learn new skills independently, and confidence in acquiring new mathematical and machine learning tools as needed.

To apply, candidates must submit a formal application for the DPhil in Chemistry via the Oxford online application system, quoting CV/Chem/2026 under ‘Departmental Studentship Applications’. The application deadline is 12.00 noon UK time on 30th March 2026. For further information about the research group, visit the Vallance group website. For eligibility criteria, refer to the UKRI website. Queries regarding the application process can be directed to [email protected].

This studentship offers a unique opportunity to contribute to cutting-edge research at the interface of chemistry, medicine, and data science, with real-world impact on surgical practice and patient outcomes.