PhD in Biology

Interested in AI and biology? Then this PhD studentship could be for you!/nThousands of donated organs are discarded each year because current preservation methods allow storage for only a few hours. Cryopreservation at ultra-low temperatures offers the prospect of long-term organ banking, but its application to large tissues and organs is limited by ice crystal formation and the toxicity of existing cryoprotective agents (CPAs). Overcoming these challenges is a major unmet need in biomedicine./nThis interdisciplinary PhD project aims to develop AI-driven approaches to discover safer and more effective CPAs by integrating machine learning, computational modelling, and experimental validation. The successful candidate will receive training in both computational and experimental biology within a highly collaborative research environment./nThe project will begin with the construction of a curated database from the literature, capturing known CPAs, their properties, concentrations, and performance across different biological systems. Machine-learning methods inspired by modern drug-discovery and network pharmacology approaches will then be applied to identify patterns and predict promising novel CPA candidates./nTo gain mechanistic insight, the student will use AI-based methods to investigate CPA–water interactions and ice inhibition. At larger scales, agent-based modelling using the BioDynaMo platform will be employed to simulate CPA diffusion and biophysical processes in three-dimensional biological systems, supporting the optimisation of CPA concentrations and administration protocols./nThe project includes training in experimental cryobiology, enabling the student to contribute to targeted in vitro validation of computational predictions. The work is further supported by an industrial partnership with Oxford Cryotechnology Ltd, providing translational context and exposure to real-world cryopreservation challenges./nThis studentship offers an excellent opportunity to develop expertise in computational biology, machine learning, molecular modelling, and experimental cryobiology, while contributing to a high-impact research area with relevance to future organ banking and transplantation.