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

University of Plymouth

Qualification Type:	PhD
Location:	Plymouth
Funding for:	UK Students, International Students
Funding amount:	The studentship is supported for 3.5 years and includes Home tuition fees plus a stipend of £21,805 per annum 2026-27 rate
Hours:	Full Time

Placed On:	2nd April 2026
Closes:	24th April 2026

Integrating Multi-Modal Radiomics and AI Co-Pilot Software to Accelerate Cancer Detection and Improve Treatment Decision-Making

DoS: Dr Vassilis Cutsuridis (vassilis.cutsuridis@plymouth.ac.uk)
2nd Supervisor: Mehdi Saberi (msaberi.radiotherapy@outlook.com)
3rd Supervisor: Ram Shanmugasundaram (ram@ukprotontherapy.co.uk)

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

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.

To apply for this position please click on the Apply button above.

Please see here for a list of supporting documents to upload with your application.

For more information on the admissions process generally, please contact research.degree.admissions@plymouth.ac.uk