Research Fellow Full-time

Research Fellow

The Centre for Translational Genomics focuses on discovering genotype-phenotype relationships through multi-omics and disease outcome data from population and patient cohorts. We employ deep-learning and machine learning, statistical genetics, bioinformatics, and computational biology methods to organise, interpret, and apply data to support precision medicine. A key focus is on polypharmacy and influence of rare and common genetic variants, and the interplay between environmental factors and disease outcomes. The role is set within a vibrant research environment, with related work ongoing at the Institutes of Cardiovascular Science and Health Informatics. This includes expertise in health data science, Mendelian randomization, and rare loss-of-function genetics.

Cardiovascular disease is the leading cause of morbidity in ageing populations, with disease patterns in older age differing substantially from those seen in mid-life. Conditions such as atrial fibrillation become increasingly prevalent and contribute disproportionately to disability, healthcare utilisation, and loss of independence. Due to the co-occurrence of multiple cardiovascular conditions, people are often prescribed multiple medicines (i.e. polypharmacy), which together can alter drug metabolism and treatment effects, particularly in people who carry pharmacogenetic variants. For this role, we are seeking a candidate with a keen interest in applying and extending existing computational pipelines for common and rare (whole genome sequencing) genetic data to identify people who are carriers of pharmacogenetic variants and link this to electronic healthcare records data containing information on drug prescriptions and disease outcomes. The successful applicant will have access to large-scale population biobanks (including UK Biobank, All of Us, and Our Future Health), and in-house developed bioinformatics tools. The appointed candidate will be supported in developing a research profile at the interface of genomics and electronic health records. There will also be opportunities to further advance analytical and/or software development skills, with a focus on creating and maintaining computational tools for the broader scientific community. This role is funded for 2 years in the first instance.

This role is well suited to individuals with a computational background in human genetics and electronic healthcare records. The ideal candidate will hold a PhD, or possess equivalent experience, in health datascience, computer science, medicine, or a related discipline. We are seeking someone with a demonstrable track record in research and a high level of proficiency in quantitative analysis. Experience with large-scale data analysis on Unix/cloud-based systems is essential. You will be self-motivated, resourceful, and capable of working independently, while also contributing effectively as part of a collaborative team. We place a strong emphasis on supporting career development and fostering research independence.

As well as the exciting opportunities this role presents, UCL offer some great benefits, some of which are: 41 Days holiday (27 days annual leave 8 bank holiday and 6 UCL closure days), Additional 5 days' annual leave purchase scheme, Defined benefit career average revalued earnings pension scheme (CARE), Cycle to work scheme and season ticket loan, Immigration loan, Relocation scheme for certain posts, On-Site nursery, On-site gym, Enhanced maternity, paternity and adoption pay, Employee assistance programme: Staff Support Service, Discounted medical insurance. Visit https://www.ucl.ac.uk/work-at-ucl/reward-and-benefits to find out more.

As London's Global University, we know diversity fosters creativity and innovation, and we want our community to represent the diversity of the world's talent. We are committed to equality of opportunity, to being fair and inclusive, and to being a place where we all belong. We therefore particularly encourage applications from candidates who are likely to be underrepresented in UCL's workforce. These include people from Black, Asian and ethnic minority backgrounds; disabled people; LGBTQI+ people; and for our Grade 9 and 10 roles, women.