Research Associate in Deep Learning and AI for Genomics – Bornelöv Group (Fixed Term)
We are seeking a Research Associate with strong quantitative and computational skills to join the Bornelöv Lab, Department of Biochemistry, University of Cambridge.
Overview
The role focuses on applying recently developed deep‑learning and AI‐based methods to uncover the molecular mechanisms behind mRNA processing and fate, specifically examining how codon‑usage bias and other mRNA features influence gene regulation, localisation, stability and translation.
Key Responsibilities
* Develop and apply modern sequence‑based deep‑learning models to investigate the impact of codon usage and nucleotide sequence on mRNA fate.
* Analyse and interpret project data using GPU‐based compute and high‑performance computing resources.
* Collaborate with the computational team led by Dr Susanne Bornelöv and engage in complementary approaches including evolutionary genomics and bioinformatics.
* Shape the direction of the project and formulate own research questions within the scope of codon‑usage bias and mRNA regulation.
Qualifications
* PhD (or final‑year PhD student) in a relevant quantitative discipline.
* Strong experience in deep‑learning and machine‑learning techniques applied to biological data.
* Proficiency in programming and scripting.
* Independent project ownership and strong quantitative analytical skills.
* Genuine interest in fundamental molecular biology principles, with prior work in gene regulation (e.g., mRNA transcription, translation or turnover) considered highly beneficial.
Fixed‑Term Details
The position is funded from 1 June 2026 to 31 May 2029.
Equal Opportunity
The University actively supports equality, diversity and inclusion and encourages applications from all sections of society. The University has a responsibility to ensure that all employees are eligible to live and work in the UK.
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