PhD Studentship: AI-assisted design of cryoprotective agents or tap here to enter text

Interested in AI and biology? Then this PhD studentship could be for you! Thousands 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.

This 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.

The 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.

To 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.

The 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.

This 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.

Supervisors: Dr Roman Bauer, Dr Xilu Wang, Prof Kamalan Jeevaratnam and Prof Joao Pedro de Magalhaes    

Entry requirements

Open to UK nationals only. Starting in July 2026.

Later start dates may be possible, please contact Dr Roman Bauer once the deadline passes.

You will need to meet the minimum entry requirements for our PhD programme.

A strong background in computer science, computational science, data science, or a closely related discipline is expected, with an interest in applying computational and AI-based methods to interdisciplinary biomedical research. Experience or interest in machine learning, programming, or computational modelling is desirable, as is a willingness to engage with experimental collaborators in a multidisciplinary research environment.

How to apply

Applications should be submitted via the Computer Science PhD programme page.

In place of a research proposal, you should upload a document stating the title of the project that you wish to apply for and the name of the relevant supervisor. Prospective applicants are welcome to contact Dr Roman Bauer for informal enquiries and further information about the project.

Funding

Funded in competition with multiple projects. Funding is for 3.5 years.

Funded by EPSRC and co-funding from Oxford Cryotechnology Ltd.

Application deadline: 9 March 2026

Enquiries: Contact Dr Roman Bauer

Ref: PGR-2526-018

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