PhD Studentship - Deciphering Kinase Selectivity and Regulation to Develop a Toolkit for Studying the ‘Dark’ Kinome

Project Supervisors: Dr. Vibhu Jha, Prof. Sherif El-Khamisy, Dr. Gareth Evans, Dr. Martin McPhillie

Project description:

About the Project – The Challenge: Illuminating the ‘Dark Kinome’

The human genome encodes more than 500 protein kinases, which act as central control points for cell growth, communication, and stress responses. Yet over 100 of these kinases are almost completely uncharacterised, the so-called ‘Dark Kinome’. These knowledge gaps limit our understanding of signalling networks, and emerging evidence links several of these understudied kinases to ageing, cancer, and neurodegenerative disease.

This PhD project aims to bring the dark kinome into the spotlight by combining advanced AI-driven prediction with cutting-edge chemical biology. The goal is not only to understand how these kinases function, but to develop the molecular tools the global research community needs to investigate them. This is fundamental, high-impact bioscience with the potential to unlock new therapeutic strategies.

Unique experimental toolkit:

This project is grounded in a strong cross-institutional collaboration, providing training across computational biology, structural biochemistry, and chemical biology. You will develop a rare and highly sought-after skillset, valued in academic research, biotechnology, and pharmaceutical discovery. By integrating multiscale modeling with experimental validation, you will uncover how sequence and structural variation shape kinase activity and substrate selectivity, and apply these insights to the dark kinome, generating the first molecular tools to probe these understudied enzymes.

What you will do (Research Objectives):

1. Use structural modeling and simulations (QM/MM, MD) to identify features controlling kinase activation and substrate selectivity in exemplar systems (EGFR, Src).
2. Develop a machine learning platform to predict regulatory mechanisms in dark kinome targets (e.g., PKMYT1, RIOK1/2).
3. Perform biochemical validation, including recombinant protein expression and phosphorylation assays.
4. Work with chemists to design fluorescent and biochemical probes, enabling real-time monitoring of kinase activity in living cells.

Training & Environment

This project offers exceptional interdisciplinary training, suitable for candidates from biochemistry, molecular biology, computational biology, chemistry, or data science backgrounds.

You will gain experience in:

1. Molecular modeling, QM/MM & MD simulations
2. AI/ML methods for biomolecular prediction
3. Kinase biochemistry, mutagenesis and assay design
4. Protein-protein interaction and phosphorylation network analysis
5. Chemical biology & probe development

There will be opportunities for short research exchanges or secondments to gain hands-on experience in specialised structural biology or computational laboratories (supported by High Performing Computing Cluster), ensuring maximum exposure to diverse research environments. You will pioneer computational biochemistry, machine learning and novel kinase profiling tools, ultimately identifying putative targets for next-generation therapies.

Funding notes:

This project has full funding for UK students, which will cover tuition fees, a tax-free stipend of £20,780 per year for living costs, and a Research Support Grant.

Funding for: UK Students

Enquiries email name and address:

For informal enquiries, please contact v.jha2@bradford.ac.uk

How to apply: Potential candidates should apply directly online through the online application portal.

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