AVÊÓƵ

Life Sciences PhD Biochemistry: AI solutions to guide treatment strategies for Cancers of Unknown Primaries (CUPs) (2025)

What you get

This is a 3.5-year PhD studentship funded in the Sussex Cancer Research Centre, funded by Brighton and Sussex Medical school and the AVÊÓƵ School of Life Sciences, starting on 1st October 2025. Funding will cover tuition fees for UK students (at the Home rate), a stipend at the UKRI rate, and consumables. International applicants are welcome to apply but will be required to cover the difference between Home and International fees.

Type of award

Postgraduate Research

PhD project

In general, the types of treatment available to a cancer patient is determined by the type or ‘site’ of the original tumour. However, for 3-5% of all cancers, termed 'cancer of unknown primary' or 'CUP’s,' the original tumour site is unknown, making it particularly challenging to decide on the best treatment strategy for the disease as it presents at diagnosis, in secondary sites. For a minority of CUP patients (15–20%), the tumour can be attributed to a distinct clinical entity that benefits from primary site-specific treatment; however, the remaining 80–85% of patients belong to a group with a poor CUP prognosis.  In Sussex, despite extensive clinical and diagnostic work-up, including physical examination, radiological imaging, and histopathological investigation, approximately 300-500 of the cancers diagnosed annually, are designated as CUPs. 

The major aim of this proposal is the development of artificial intelligence (AI) methods to aid the diagnosis and inform treatment strategies to improve the outcome for Sussex CUP patients. 

 Research Environment:  This project is a collaboration between the bioinformatics group at the AVÊÓƵ, Brighton and Sussex Medical School (BSMS) and the CUP Multi-Disciplinary Team (MDT) at the Royal Sussex County Hospital (RSCH), University Hospitals Sussex NHS Foundation Trust.  At Sussex the student will be trained in genomics, programming, bioinformatics, big data and data science, cancer biology and therapeutics.  They will attend weekly online MDT meetings with the CUP team and will be trained in the interpretation of pathology and radiology outputs, at the RSCH and/or Brighton and Sussex Medical School.

Eligibility

The ideal candidate would have a first degree in Life Sciences (e.g. Biochemistry, Biomedical Sciences etc) and a Master’s degree in a computation discipline (e.g. Bioinformatics, Data Science etc) or a proven ability in computer programming.  Alternatively, the project would suit a candidate from a mathematical or computation discipline (e.g. Computer Science, Maths, Statistics, Data Science) who is happy to be trained in cancer biology.  You may also be considered for the position if you have other professional qualifications or experience of equivalent standing.

Candidates for whom English is not their first language will require an IELTS score of 6.5 overall, with not less than 6.0 in any section or equivalent proficiency - English language requirements

Applications are particularly welcomed from candidates with protected characteristics – e.g., from Black and other ethnic minorities – who are under-represented in postgraduate research at our institution.

Deadline

How to apply

Please submit a formal application using the online admissions portal attaching a CV, degree transcripts and certificates, and two academic referees. A research proposal is not required. Instead, please upload a personal statement describing your subject areas of interest, skills and previous experience, motivation for Doctoral Research, future goals, and why you are applying to this project.

On the application system select Programme of Study – PhD Biochemistry. Please select ‘funding obtained’ and state the supervisor’s name where required.

Interviews will be held in February 2025.

Informal enquiries are welcome and should be submitted to Dr Frances Pearl at f.pearl@sussex.ac.uk

Contact us

For queries about the application process, please see the online application guide or
contact Emma Chorley: lifesci-rec@sussex.ac.uk 

For enquiries about the project, please contact Frances Pearl: f.pearl@sussex.ac.uk