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University of Cambridge

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PhD in Understanding Gene Regulation through Computational and AI-based Methods University of Cambridge in United Kingdom

Degree Level

PhD

Field of study

Computer Science

Funding

This is not a funded PhD programme. Candidates must secure their own funding. Successful applicants may be supported to apply for local funding competitions such as Cambridge Trust or Gates Cambridge, and additional funding schemes, including overseas options where applicable.

Deadline

Dec 8, 2026

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Country

United Kingdom

University

University of Cambridge

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Keywords

Computer Science
Molecular Biology
Evolutionary Biology
Biology
Artificial Intelligence
Computational Biology
Comparative Genomics
Rna Biology
Transcriptional Regulation
Genomic
Statistics
Bioinformatic
ML

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About this position

PhD opportunity at the University of Cambridge in the Department of Biochemistry with Dr Susanne Bornelöv.

This project focuses on gene regulation, bioinformatics, machine learning, artificial intelligence, genomics, and molecular biology. The Bornelöv lab studies transcriptional and posttranscriptional regulation, including codon usage, codon optimality-mediated mRNA decay, genome organisation, and evolutionary genomics. The work combines multi-omics data analysis, comparative genomics, ribosome profiling, explainable AI, and deep learning. There is also scope to use Drosophila as a model system and, if desired, contribute to experimental validation.

Potential research directions include codon-level prediction of translational efficiency, explainable AI for gene regulation, comparative codon usage across the tree of life, tRNA supply and demand, RNA-focused foundation models, design of new regulatory elements, and the impact of transposable elements on gene regulation.

Eligibility: applicants should have a background in computational or systems biology, bioinformatics, computer science, or a related field. Strong coding/computational skills are important. Candidates from molecular biology or biochemistry are also welcome if they can show clear computational ability and interest.

Funding: this is not a funded PhD; applicants must secure their own funding. The successful candidate may be supported to apply for Cambridge Trust, Gates Cambridge, and other funding schemes.

How to apply: email [email protected] with subject “SBlab-PhD2027” and include transcripts, CV, statement of interest, brief research proposal, and two academic references. Interested applicants should contact the supervisor at least a month before the funding deadlines. The University of Cambridge funding deadline is 8 December 2026, with an earlier Gates Cambridge deadline for US applicants on 14 October 2026.

Funding details

This is not a funded PhD programme. Candidates must secure their own funding. Successful applicants may be supported to apply for local funding competitions such as Cambridge Trust or Gates Cambridge, and additional funding schemes, including overseas options where applicable.

What's required

Applicants should have a degree in computational or systems biology, bioinformatics, computer science, or a related discipline. Candidates from molecular biology or biochemistry backgrounds are also encouraged if they can demonstrate strong computational skills and interest. The post seeks someone with good computer and coding skills and a keen interest in computational molecular biology, machine learning, and fundamental cell biology.

How to apply

Email [email protected] with the subject line “SBlab-PhD2027”. Include transcripts, a CV, a statement of interest, a brief research proposal, and contact details for two academic references. After initial contact, selected applicants will be invited to submit a formal application through the University of Cambridge Application Portal before the funding deadline.

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