This project offers an exciting opportunity to combine AI and computational biology to build cutting-edge digital tumour twins; computational models that mimic the behaviour of individual tumours to optimise cancer treatment. You will develop advanced supervised and self-supervised deep learning technologies that integrate a patient’s medical history, demographics, and microscopic tumour characteristics derived from histopathology. By creating age- and gender- matched models, you will explore the diverse trajectories of disease in patients with similar profiles.
A key innovation of this project is the integration of spatial and single-cell proteomics, enabling unprecedented insights into tumour architecture at cellular and tissue levels. Moreover, you will have access to experimental 3D tumour spheroids and organoid models to validate and refine your digital twins, ensuring that your predictions are grounded in real-world biology. These unique datasets will allow the development of reliable model with real-world value.
Through your studies you will gain expertise in AI, computational biology, experimental medicine research and recent digital twins frameworks.

