Imaging science is a relatively new branch of applied mathematics for emerging applications in almost all areas of cutting-edge research. The field is growing rapidly as new technologies are constantly driving the development.

This imaging project is an opportunity to undertake one of our new and exciting cross-disciplinary projects lying at the interface of mathematics and cancer medicine. The candidate does not need to have any knowledge in cancer diseases or medicine but will need strong mathematical knowledge through a degree in maths, or in computer science / physics / engineering with essential maths components, as well as good programming skills.

This multidisciplinary project aims to address a key step in designing new drugs and testing their efficacy is a comprehensive understanding of disease mechanisms at the single-cell and tissue context level. Working with teams from Astra-Zeneca, we investigate a range of biomedical imaging modalities and study cellular heterogeneity and the intricate interactions in disease microenvironments to chart cellular heterogeneity, complex tissue structures, and dynamic changes during diseases progression.

In terms of research and development, it addresses a set of outstanding challenges in both mathematical and AI fields. Working with applied mathematicians from Strathclyde and computing scientists from Queen’s University of Belfast, along with AI and data analysis teams from AZ, the successful student will get a thorough training in Mathematical Imaging (e.g variational models and diffeomorphic maps), Artificial Intelligence (neural networks and transfer learning),  Biomedical Research (Multimodal imaging, transcriptomics and H&E) and gain practical problems solving skills that are highly values in both Academia and Industries. Through the supervisors’ contacts and networks, the student will also benefit from and apply his or her skills to discussions and potential collaborators with other Universities including Universities of Birmingham and Liverpool and NHS hospitals such Clatterbridge Cancer Centre.  

Overall, this studentship is attractive because the topic under study is interesting and modern and a candidate has the flexibility to focus on all or just one of the key components:  maths, AI and biomedical analysis in terms of leading research. Apart from the collaboration opportunity with a top UK company, there is a ready secondary supervisor (Prof Styles) at QUB with complementary expertise and  also a large collaborating network.