School of Computing and Mathematical Sciences

Life and health sciences

The life and health sciences research theme brings together computer scientists, applied mathematicians, data scientists, and artificial intelligence (AI) researchers (and everyone in between) from across our School with the endeavour to serve the biology and health science communities. We offer innovative AI methodologies and advanced computational modelling techniques to real-world problems.

Our interests span from fundamental biomedical research to practical issues in community wellbeing and public health initiatives, at scales ranging from molecules and genomes, through cells, tissues, and organs, to emerging aspects in environment and populations. Our vision is to innovate by using novel means to efficiently interrogate big data, integrate domain expert knowledge, and provide explanations of AI predictions. Our motivation is a desire to better understand the biological world and help improve livelihoods.

Key research areas

  • AI-powered biomedical image analysis.
  • Digital twins, simulations, and compute intensive methods.
  • Ecological modelling and population dynamics.
  • Health data research and explainable analysis of molecular biology and omics data.


We work with local, national and international organisations and with partners across the University (including the Institute for Precision Health and the AIDAM Research Centre, among others) to deliver effective results.

Biosciences meet AI

AI is a group of recent computational approaches for prediction, inference, and design capable of harnessing large and complex data sets. AI includes, but is not limited to, machine learning, deep learning, neural networks, and other related computing technologies.

AI complements bioscience research by:

  1. Delivering solutions driven by multimodal, sparse, and heterogeneous data.
  2. Advancing our understanding of the rules of life, identifying biological principles and mechanisms using data-driven approaches.
  3. Addressing challenges and megatrends in agriculture, food security, and food safety. Key challenges include reaching net zero for mitigation of the impact of climate change, scaling up robotics and smart agriculture, improving soil and plant health.
  4. Helping professionals to manage, understand, and improve human health. Key aspects include ageingnutritionhealth inequalitiesAMR (antimicrobial resistance), and environmental and animal health in a global One Health perspective.


Recent grant successes

AI driven digital twins for net zero (EP/Y00597X/1) and clinical care (EP/Y018281/1). Deep learning in cell line authentication (EP/Y019393/1).

Contact us

Please get in touch to explore research ideas and identify funding opportunities.

Dr Robert C Free
Dr Massimo Cavallaro
Professor Ruslan Davidchack
Professor Ashiq Anjum

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