Overview
This project is based at the University of Liverpool and focuses on using artificial intelligence and machine learning to study cellular morphology during infection with high-consequence viruses such as SARS-CoV-2, MERS, and Ebola. The student will employ confocal and live-cell imaging, sequencing, and AI techniques to quantify and analyse how viruses manipulate cells and to evaluate the effectiveness of medical countermeasures.
About this opportunity
This studentship is aligned with the EPSRC Centre for Doctoral Training and is based within the Signal Processing Group. It offers access to supercomputing facilities, collaboration with leading experts, and interdisciplinary training in areas such as image processing, data fusion, and autonomy. Laboratory work will take place at biosafety levels 2 and 3, primarily under the supervision of Prof. Julian Hiscox, with research visits to the Defence Science Technology Laboratory (Dstl). This position is open to UK citizens only.
Key Highlights:
- Interdisciplinary Focus – Combines virology, cell biology, and AI/machine learning to study high-risk viruses and their cellular impact.
- Advanced Technologies – Utilises cutting-edge tools such as confocal/live-cell imaging, sequencing, and AI for cellular morphology analysis.
- High-Level Biosafety Training – Hands-on experience working in containment levels 2 and 3 – a rare and valuable skill set.
- Real-World Impact – Contributes to national defence and public health by evaluating medical countermeasures against deadly viruses.
- Prestigious Supervision & Collaboration – Led by Prof. Julian Hiscox, with joint research at the University of Liverpool and Dstl.
Viruses such as SARS-CoV-2, its more deadlier relation, MERS-coronavirus and other viral threat agents, such as Ebola virus, can have devastating health consequences. All viruses need to infect cells in order to replicate genetic material and release hundreds to thousands of new viruses. Medical countermeasures such as anti-viral drugs are designed to either block infection thus preventing the virus from entering the cell or inhibit replication of viral genetic material in the cell or prevent progeny viral exit and release. Different viruses have different strategies for cell entry and replication and also the way in which they manipulate the cell to create viral factories to enhance replication.
This project will use state of the art confocal and live cell imaging to study the morphology of cellular change during viral infection. Part of the translation rationale for the project is to assess the efficacy of medical countermeasures and whether they can reverse the effects of cellular damage – or if there is a tipping point beyond which a cell will always die. Cellular morphology is intimately related to cellular health. Artificial intelligence (neural networks) and machine learning will be an integral part of the project in order to quantify the morphologies of cellular change during infection.
The project will involve working at containment levels 2 and 3, imaging, sequencing, cell biology, virus infection, and utilising AI/machine learning approaches.
The project is supervised by Prof. Julian Hiscox (Professor of Infection and Global Health and Dean of Institute) and Prof. Simon Maskell (Professor of Autonomous Systems) at the University of Liverpool and Prof. Graeme Clark and Dr. Dominic Jenner at the Defence Science Technology Laboratory (Dstl). The work will mainly be based in the laboratory of Prof. Hiscox with research visits to Dstl. Prof. Hiscox is an experienced PhD supervisor and has taken 41 PhD students through to the successful completion of their PhD.
This is PhD is restricted to UK citizens.