PhD Studentship: Integrating Multi-Modal Radiomics and AI Co-Pilot Software for Accelerated Cancer Detection and Improved Treatment Decision-Making University of Plymouth in United Kingdom

[Full Home tuition fees, bench fee, and a stipend of £21,805 per annum (2026/27 rate) for 3.5 years. International applicants must cover the difference between Home and International tuition fees, but the international component may be waived for outstanding candidates. No additional funding for NHS Immigration Health Surcharge, visa, or flights.]

This PhD studentship at the University of Plymouth offers an exciting opportunity to advance cancer detection and treatment decision-making through the integration of multi-modal radiomics and artificial intelligence (AI) co-pilot software. Supported by EPSRC funding for 3.5 years, the project aims to develop and validate an innovative AI system that leverages radiomic data from various imaging modalities—including CT, MRI, PET, and ultrasound—to enhance diagnostic speed and accuracy in clinical oncology settings.

The research objectives include creating frameworks for extracting and integrating radiomic features, designing advanced AI algorithms for early-stage cancer detection, developing user-centric AI co-pilot software with real-time clinical decision support, and building evidence-based treatment recommendation systems. The project will undergo rigorous clinical validation through both retrospective and prospective studies, assess generalizability across diverse populations and resource settings (with a focus on low-income countries), and address ethical, regulatory, and data privacy considerations for clinical deployment.

Successful candidates will join a collaborative research environment, working under the supervision of Dr Vassilis Cutsuridis, Mehdi Saberi, and Ram Shanmugasundaram. The project is expected to produce novel AI methodologies, commercially viable software for global cancer centre networks, and accessible cancer care solutions for resource-limited healthcare environments, ultimately contributing to reduced global health disparities.

Eligibility requirements include a first or upper second-class honours degree in a relevant subject, preferably with a Master’s qualification. Essential skills are strong programming experience in Python or Matlab, data analysis, research experience, solid background in machine learning and AI, and familiarity with imaging data analysis. The ideal candidate should demonstrate a collaborative approach, curiosity, and motivation for the research topic. Applications are welcome from both UK and overseas students; however, the studentship fully funds only those eligible for Home fees. Outstanding international applicants may have the international fee component waived, but must cover any remaining costs such as NHS Immigration Health Surcharge, visa, and travel expenses.

The studentship covers full Home tuition fees, bench fee, and a stipend of £21,805 per annum (2026/27 rate) for 3.5 years. The subsequent 6 months of registration is a self-funded ‘writing-up’ period. Applicants cannot work full time while receiving the PhD stipend.

To apply, click the Apply button on the position page and upload all required supporting documents. For informal discussions about the project, contact Dr Vassilis Cutsuridis. For admissions process queries, email [email protected]. The application deadline is 24 April 2026 at 12 noon, and shortlisted candidates will be invited for interview shortly thereafter.