We are seeking a motivated and enthusiastic Research Scientist with strong AI/machine learning expertise to join the research group of Professor Jim Hughes. The primary focus of the project is to identify causal non-coding changes in the human genome and their linked genes which underlie a spectrum of common diseases. The initial focus will be on non-coding genetics of the haematological cellular niche.
You will be involved in designing, developing and implementing high-throughput bioinformatics and machine-learning solutions to analyse large-scale genomic and transcriptomic datasets (bulk and single-cell), with the aim of linking DNA sequence and chromatin features to gene regulation and expression. You will translate mathematical and AI concepts into robust, well-engineered pipelines that run reproducibly at scale on HPC/cloud environments, with emphasis on interpretability, uncertainty estimation and generating mechanistic hypotheses.
You will hold a postgraduate degree (MSc) or greater in computer science, bioinformatics, or a related computational discipline with experience and demonstrable background in analysing complex biological data. Essential requirements include expertise in machine learning libraries (TensorFlow, Keras, and PyTorch), strong programming skills (Python and R), experience with statistical and mathematical methods for AI in high-dimensional spaces, and proficiency in developing reproducible computational pipelines for HPC/cloud environments. Experience with AI explainability methods, Git repositories, GPU acceleration, and the ability to draft manuscripts for publication are also required.
The post is available fixed-term for 12 months, funded by the Wellcome Trust.
Applications for this vacancy are to be made online. You will be required to upload a CV and supporting statement as part of your online application.
The closing date for this position is 12:00 noon on Wednesday 01 October 2025. Interviews will be held in October 2025.