"Research Assistant"

About the role

As a Research Assistant in Statistics and Genetic Epidemiology, you will play a key role in supporting a highly successful and internationally recognised research group. You will contribute to statistical, genetic and genomic epidemiology projects that underpin drug development, working with large-scale genomic and linked health data, including major cohort studies and biobank resources. Your work will support high-impact programmes such as research into chronic diseases within the EXCEED Cohort Study, as well as investigations into the genetic basis of respiratory disease, including an £8.8 million Wellcome Trust Discovery Award focused on lung function impairment. You will also engage in collaborations aimed at advancing drug safety, repurposing, and development with academic and industry partners.

This role offers the opportunity to develop your technical and analytical skillset while contributing to high‑quality research outputs. You will take part in data analysis, interpretation, and dissemination activities, including workshops and conferences. Working closely with colleagues across the Genetic Epidemiology Group, you will help achieve project milestones and contribute to publications and knowledge exchange. You will join a collaborative environment committed to training, development and capacity‑building, supported by major funders including the Wellcome Trust, MRC, NIHR and industry collaborators.

About you

You will hold an Honours degree or equivalent experience and bring knowledge of epidemiological study design alongside sound statistical skills. You will have good programming ability in R or equivalent analytical software and be able to apply statistical methods to large datasets with accuracy and initiative. You will demonstrate enthusiasm for research, excellent communication skills, and the ability to work both independently and within a multidisciplinary team. Your commitment to professional development will be key, particularly as you expand your expertise in statistical genetic analyses.

Ideally, you will also bring experience or training in areas such as medical statistics, UNIX systems, bioinformatics, or human genetics, though we welcome candidates eager to develop in these areas. You will be organised, able to balance priorities, and comfortable managing your workload to meet research objectives. As a member of the University community, you will  contribute to a positive and collaborative research culture that supports open enquiry and diverse perspectives.