This PhD project aims to investigate how liver cancer morphology evolves under treatment, over time. Working with a unique collection of patient samples taken both before and after therapy, you will apply our state-of-the-art AI methodologies to chart how tumour structures evolve over time. You will then integrate these findings with spatial transcriptomics, a powerful technology that measures which genes are actively expressed in different regions of the tumour while preserving their spatial context.

By combining AI with spatial biology, you will uncover the molecular programs that drive therapy resistance and develop the first computational model to simulate this evolutionary process. This interdisciplinary project brings together cancer biology, pathology, and AI with the ultimate goal of identifying new ways to predict treatment failure and design more effective therapies.

This PhD project aims to investigate how liver cancer morphology evolves under treatment, over time. Working with a unique collection of patient samples taken both before and after therapy, you will apply our state-of-the-art AI methodologies to chart how tumour structures evolve over time. You will then integrate these findings with spatial transcriptomics, a powerful technology that measures which genes are actively expressed in different regions of the tumour while preserving their spatial context.

By combining AI with spatial biology, you will uncover the molecular programs that drive therapy resistance and develop the first computational model to simulate this evolutionary process. This interdisciplinary project brings together cancer biology, pathology, and AI with the ultimate goal of identifying new ways to predict treatment failure and design more effective therapies.