PhD Studentship - Use of Genome-wide CRlSPR Screening and Machine Learning Touncover Novel Therapeutic Approaches for Advanced Metabolicliver Disease and Type 2 Diabetes

Research theme: Bioinformatics, Machine learning, Healthcare

How to apply: uom.link/pgr-apply-2425

Number of positions: 1

This 3.5 year PhD is fully funded. The successful applicant will receive an annual tax free (depending on circumstance) set at the UKRI rate (£19,237 for 2024/25). Tuition fees will also be paid. This PhD is a dual-award between The University of Manchester and The University of Melbourne.

Metabolic dysfunction-associated steatotic liver disease (MASLD) is the most common chronic liver condition in developed countries, with a global prevalence of 30%. The severe form of MASLD, MASH (metabolic dysfunction-associated steatohepatitis), is characterised by fat accumulation, inflammation and frequently fibrosis in the liver, and increases the risk of developing life-threatening liver cancer. In addition, 70% of individuals with type 2 diabetes (T2D) have MASLD, and thereby a 2.5-fold greater mortality risk. Despite this global epidemic, the first therapy for MASLD was only provisionally approved for human use in the USA in 2024, and new approaches are urgently needed.

Lipid accumulation in the liver is a primary driver of MASLD, and various therapies currently in clinical trials focus on reducing lipid accumulation for the treatment of advanced liver disease. Using a comprehensive genetic screen in liver cells, we identified thousands of novel regulators of lipid metabolism highly relevant for therapeutic targeting.

Based on this genetic screen, this PhD project will focus on the development of machine learning algorithms to predict and pinpoint the most important regulators of lipid metabolism in the liver, and their impact on systemic blood glucose control. Specifically, this PhD project will focus on the development of machine learning approaches to predict the ability of the proteins identified in the genetic screen to regulate lipid accumulation and glucose metabolism in the liver, components of the project that will be carried out at The University of Manchester. This will be accompanied by testing the metabolic impact of the top candidate(s) in cell and/or mouse models of metabolic disease, which will be carried out at The University of Melbourne. Together, this project will forecast the effects of novel candidates on MASLD and T2D progression and will allow for effective therapeutic validation.

Applicants should have, or expect to achieve, at least a 2.1 honours degree or a master’s (or international equivalent) in a relevant science or engineering related discipline.

If you apply for the Manchester-based position, please get in touch with hongpeng.zhou@manchester.ac.uk for more information.

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