Multi-Modal AI and End-to-End Image Analysis for Oncological Imaging in Lung Cancer

About the Project

We are seeking an outstanding PhD student to join the POLARIS/SPIRO group at the University of Sheffield to develop next-generation Artificial Intelligence (AI) and image analysis tools for lung cancer imaging.

Lung cancer is the leading cause of cancer death worldwide. Advanced imaging techniques – including dynamic contrast-enhanced MRI, hyperpolarised MRI, and photon-counting CT – provide unprecedented information about tumour biology and treatment response, but translating this into clinical practice requires fast, robust, and automated analysis tools.

In this project you will develop multi-modal AI methods spanning classical image processing, deep learning, and hybrid approaches for segmentation, registration, image synthesis, and treatment response prediction in lung cancer. You will access unique datasets from the POLARIS imaging laboratory and Weston Park Cancer Centre, and work within the SPIRO (Sheffield Platform for Imaging Research in Oncology) programme – a £4M+ Yorkshire Cancer Research infrastructure platform.

This project is ideal for candidates who want to apply AI methods to solve real-world clinical problems, and you will work closely in a multidisciplinary environment that bridges cutting-edge health technologies, AI development and clinical problem-solving.

You will gain expertise in both classical and AI-based image analysis, advanced lung MRI and CT, and clinical oncological research within a world-leading imaging group with strong NHS clinical partnerships and an excellent track record of PhD completions.

Entry Requirements:

Candidates should hold, or expect to hold, a first or upper second class honours degree (or equivalent) in medical physics, engineering, computer science, mathematics, or a related physical or computational discipline. Strong programming experience (Python preferred) is essential.

Experience in medical imaging, machine learning, biomedical engineering or image analysis is desirable, but is not essential.

Start date: 01 October 2026

How to apply:

Please complete a University Postgraduate Research Application form available here: www.shef.ac.uk/postgraduate/research/apply

Please clearly state the prospective main supervisor in the respective box and select (School of Medicine and Population Health) as the department.

Enquiries:

Interested candidates should in the first instance contact: Dr Bilal Tahir, b.tahir@sheffield.ac.uk

Funding Notes

This award will cover home tuition fees and stipend at UKRI rate for 3.5 years supported by the Yorkshire Cancer Research SPIRO Transformative Capital Infrastructure Award.

Overseas applicants are welcome to apply, however will need to cover the tuition fee difference. Further information on tuition fees can be found on the following webpage - https://www.sheffield.ac.uk/new-students/tuition-fees/fees-lookup