A Multi-Modal Framework for Predicting and Monitoring Immuno-Radiotherapy Response in Cancer

Project ID: 2531bd1689

(You will need this ID for your application)

Research Area(s): Engineering
Physics

UCL Lead department: Medical Physics and Biomedical Engineering

Lead Supervisor: Esther Baer

Project Summary:

Cancer treatment is undergoing a revolution as we move towards highly personalised therapies. Combining radiotherapy with new immune-boosting drugs (immunotherapy) can be incredibly effective, but it only works for some patients. This project tackles this critical challenge head-on. You will develop a revolutionary AI-powered tool to predict who will benefit from treatment. Your research will empower clinicians to adapt treatment based on the patient’s immune response, helping to ensure patients receive the most effective and least toxic therapy possible.

This is a cutting-edge computational project with direct clinical impact. You will first train state-of-the-art AI models on a unique dataset of pathology slides from major clinical trials to learn the microscopic signatures of a successful immune response. You will then teach a computer to find these same signatures in patient CT scans. Finally, you will be among the first researchers in the world to apply these methods to data from a next-generation Photon-Counting CT scanner, pushing the boundaries of medical imaging.

You will join a dynamic, multi-disciplinary team at University College London, one of the world’s leading research universities. You will be supervised by Dr. Esther Bär and work closely with clinical staff at University College London Hospital.

We are looking for a highly motivated candidate with a strong background in a quantitative discipline such as physics, computer science, or engineering. Excellent programming skills (ideally Python) and a keen interest in applying machine learning to solve real-world medical problems are essential. You don’t need to be an expert in oncology, but you must have a passion for learning and a desire to work at the exciting interface of technology and healthcare.