Claire Vallance
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DPhil studentship in clinical mass spectrometry and machine learning applied to the characterisation of brain tumours University of Oxford in United Kingdom
Degree Level
PhD
Field of study
Computer Science
Funding
Available
Deadline
Mar 30, 2026
Country
United Kingdom
University
University of Oxford

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About this position
This DPhil studentship at the University of Oxford offers an exciting opportunity to conduct research in clinical mass spectrometry and machine learning, focusing on the characterisation of brain tumours. The position is based in the Department of Chemistry and supervised by Professor Claire Vallance, whose group applies atmospheric pressure and imaging mass spectrometry to both clinical medicine and fundamental chemical reaction dynamics. The project is sponsored by the Doogood Foundation and will be carried out in close collaboration with consultant pathologist Olaf Ansorge and consultant neurosurgeon Puneet Plaha at Oxford’s John Radcliffe Hospital.
Building on a successful pilot study, the research will extend the use of atmospheric pressure ionisation mass spectrometry coupled with machine learning to differentiate between brain tumours and normal tissue. The main aim is to investigate the infiltration zone forming the boundary between tumour and healthy tissue, ultimately developing improved methods for defining the surgical boundary during tumour resection. Additional related research avenues may also be explored, offering a broad scope for scientific inquiry.
The successful applicant will be based in the Chemistry Research Laboratory (CRL) at Oxford, with significant time spent at the John Radcliffe Hospital. The studentship covers course fees at the Home rate and provides a stipend of £20,780 per annum for four years, matching the UK Research Council standard. The Department of Chemistry holds the Athena SWAN Silver Award and is committed to diversity, equality, and inclusion.
Applicants should have a first-class or strong upper second-class undergraduate degree in Chemistry, medical sciences, or a related subject. Experience in mass spectrometry, statistical data analysis, machine learning, or scientific programming is advantageous but not essential. Candidates must demonstrate a strong commitment to research and the ability to learn new skills independently, including mathematical and machine learning tools.
To apply, candidates should 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, contact Professor Claire Vallance at [email protected]. Queries about the application process can be directed to [email protected]. More details about the Vallance group’s research can be found at https://vallance.web.ox.ac.uk.
Funding details
Available
What's required
Applicants should have a first-class or strong upper second-class undergraduate degree in Chemistry, medical sciences, or a related subject. Previous experience in mass spectrometry, statistical data analysis, machine learning, or scientific programming is useful but not essential. Candidates must demonstrate a strong commitment to research and the ability to learn new skills independently. Applicants should feel confident in learning and using new mathematical and machine learning tools as needed. Eligibility criteria as set out by UKRI apply.
How to apply
Submit a formal application for DPhil in Chemistry via the Oxford online application system. Quote CV/Chem/2026 under ‘Departmental Studentship Applications’. Application deadline is 12.00 noon UK time on 30th March 2026. For queries, contact [email protected].
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