Integrating multi-modal radiomics and AI co-pilot software to accelerate cancer detection and improve treatment decision-making

Applications are invited for a 3.5-year EPSRC funded UDLA PhD studentship. The studentship will start on 1 October 2026.

Apply 

To apply please use the online application form. Simply click on the online application link below for PhD Artificial Intelligence. 
Within the research section of the application form, in the following field, please add: 
‘Proposed project title/studentship title’ add EPSRC DLA 26-10 Cutsuridis.
When the application asks for a research proposal, please just upload a blank document. A research proposal is not needed for this programme as you are applying directly to a studentship project.

Application guidance 

It is important that you follow the instructions above or your application for this studentship may be missed and therefore will not be considered.
Before applying, please ensure you have read the Doctoral College’s general information on applying for a postgraduate research degree.
For more information on the admissions process please contact research.degree.admissions@plymouth.ac.uk.
Director of Studies (DoS): Dr Vassilis Cutsuridis
Second Supervisor: Mehdi Saberi
Third Supervisor: Ram Shanmugasundaram
Applications are invited for a 3.5-year EPSRC funded UDLA PhD studentship. The studentship will start on 1 October 2026.

Project description 

Project aim
To develop and validate an AI co-pilot software system integrating multi-modal radiomics data to enhance cancer detection speed and accuracy while providing evidence-based treatment decision support in clinical oncology settings.
Key objectives
This doctoral research will: (1) develop frameworks for extracting and integrating radiomic features from multiple imaging modalities (CT, MRI, PET, ultrasound); (2) design advanced AI algorithms for early-stage cancer detection with high sensitivity and specificity; (3) create user-centric AI co-pilot software with real-time clinical decision support; (4) build evidence-based treatment recommendation systems using radiomic signatures and clinical guidelines; (5) conduct rigorous clinical validation through retrospective and prospective studies; (6) assess generalizability across diverse populations and resource settings, particularly in low-income countries; and (7) address ethical, regulatory, and data privacy considerations for clinical deployment.
Expected impact
The research will produce novel AI methodologies, commercially viable software for ICRI's global cancer centre network, improved diagnostic accuracy and treatment outcomes, and accessible cancer care solutions for resource-limited healthcare environments, ultimately contributing to reduced global health disparities.

Eligibility

Applicants should have a first or upper second-class honours degree in an appropriate subject and preferably a relevant Master’s qualification. Applications from both UK and overseas students are welcome. 
The *ideal candidate* is expected to have:
  • Very good experience in programming in Python or Matlab and data analysis (essential)
  • Research experience (essential, e.g., through research MPhil/Master’s degree, or research assistant job)
  • Solid experience in machine learning and AI (essential)
  • Experience with imaging data analysis
  • A collaborative approach to doing science and willingness to help other lab members
  • Curiosity and motivation to work on the proposed or related research questions.
The studentship is supported for 3.5 years and includes full Home tuition fees, Bench fee plus a Stipend of £21,805 per annum 2026/27 rate.  The studentship will only fully fund those applicants who are eligible for Home fees with relevant qualifications.  Applicants normally required to cover International fees will have to cover the difference between the Home and the International tuition fee rates.  The international component of the fee may be waived for outstanding international applicants.
There is no additional funding available to cover NHS Immigration Health Surcharge (IHS) costs, visa costs, flights etc.
  • The studentship is supported for 3.5 years of the four-year registration period. The subsequent 6 months of registration is a self-funded ‘writing-up’ period.
  • You can’t work full time while receiving a PhD stipend.
If you wish to discuss this project further informally, please contact Dr Vassilis Cutsuridis.
How to apply
To apply, please click the ‘Online application’ link above. Please include the following documents with your application:
  • CV / résumé
  • Personal Statement (outlining your academic interests, prior research experience and reasons for wishing to undertake the project).
  • Degree certificates and transcripts (please provide interim transcript if you are still studying). 
  • Contact information for two referees familiar with your academic work.
  • If relevant, proof of English Language Competency (Applicants whose first language is not English will be required to demonstrate proficiency in the English language with an IELTS Academic of 6.5 overall with a minimum of 5.5 in each component, or equivalent).
Please also see here for a list of supporting documents to upload with your application.
For more information on the admissions process generally, please visit our How to Apply for a Research Degree webpage or contact the Doctoral College.
The closing date for applications is 12 noon on 24 April 2026. Shortlisted candidates will be invited for interview shortly thereafter. We regret that we may not be able to respond to all applications.  Applicants who have not received a response within six weeks of the closing date should consider their application has been unsuccessful on this occasion.