Research Fellow in Artificial Intelligence and Machine Learning for Scientific Discovery

Overview

The University of Manchester invites applications for a Research Fellow in Artificial Intelligence and Machine Learning for Scientific Discovery. Based in the Department of Chemistry and the School of Natural Sciences within the Faculty of Science and Engineering, the position takes place within the Chica Research Group at the Manchester Institute of Biotechnology. The successful candidate will develop and apply data-driven approaches to challenges in protein engineering and enzyme design, working alongside computational and experimental researchers to expand the group's AI capabilities and advance scientific discovery.

Who can apply

Applicants should possess expertise in artificial intelligence, machine learning, computer science, applied mathematics, statistics, or a related quantitative discipline. Candidates who enjoy working in interdisciplinary environments, are motivated to create innovative computational methods, and are enthusiastic about learning new technologies are of particular interest. Prior background in chemistry, biology, or protein science is helpful but not mandatory.

What you get

The position offers a salary ranging from £48,337 to £59,390 per annum depending on experience. Employee benefits include a generous employer contribution pension, 29 days of annual leave plus bank holidays alongside a Christmas closure, and access to a ride-to-work and electric vehicle car scheme.

Requirements

The postholder is responsible for designing, implementing, training, and evaluating predictive machine learning models, as well as analysing complex biological, chemical, and experimental datasets. Duties include developing computational tools, workflows, and software to support reproducible research, offering specialist guidance and training in data science across the research group, and collaborating on publications, conference presentations, and funding applications. Staff members are also expected to maintain high standards of software documentation and stay informed on advancements in scientific computing and artificial intelligence.

How to apply

Enquiries regarding the role, shortlisting, and interviews can be directed to David Leys. Administrative support and general questions are handled through recruitment services, and technical portal assistance is available via the online job support platform.

Key dates

The closing date for applications is 2026-11-10.