AI Research Scientist in Genomics

University of Oxford; Oxford; On-site; GBP 35,000 - 50,000; Full time

Job summary

A leading research institute in Oxford is seeking a motivated Research Scientist with strong AI and machine learning expertise. The role focuses on identifying causal non-coding changes in the human genome linked to common diseases. Candidates should have a postgraduate degree and experience in analyzing complex biological data. This position offers a unique opportunity to contribute to cutting-edge research in genomics.

Qualifications

• 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 and strong programming skills.
• Experience with AI explainability methods, Git repositories, GPU acceleration is required.

Responsibilities

• Design and implement bioinformatics and machine-learning solutions to analyze genomic datasets.
• Translate mathematical and AI concepts into robust pipelines for HPC/cloud environments.

Skills

Machine learning libraries (TensorFlow, Keras, PyTorch)

Programming skills (Python, R)

AI explainability methods

Statistical and mathematical methods for AI

Experience with Git repositories

Education

Postgraduate degree (MSc) in computer science, bioinformatics, or related field

Job description

Overview

Radcliffe Department of Medicine, MRC Weatherall Institute of Molecular Medicine, MRC Molecular Haematology Unit, John Radcliffe Hospital, Headington, Oxford. 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.

Responsibilities

• 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.
• 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.

Qualifications

• 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.