Research Fellow in pharmacoepidemiology (Grade 7-8) Full-time

Research Fellow In Pharmacoepidemiology (Grade 7-8)

We are a research team working across biomedical science focusing on integrating evidence from longitudinal electronic healthcare records with evidence from bioinformatics sources such as human genetics to identify and prioritise drug development opportunities. A key focus is the application of causal inference methods to conduct real-world pharmacoepidemiology studies evaluating drug repurposing hypotheses for prevention and management of cardiovascular diseases, including atrial fibrillation and heart failure.

As part of an ERC-consolidator project, we are seeking to appoint a full-time position, funded for 3 years initially, at the Institute of Cardiovascular Science, part of the Department of Population Science and Experimental Medicine. Cardiovascular drug development suffers from high attrition rates and expensive late-stage failures, limiting the amount of safe and effective medication reaching people in need. Medications approved for a non-cardiovascular indication may provide opportunities to explore repurposing for management of cardiovascular disease. We seek to leverage routine care electronic healthcare data to provide real-world validation of drug repurposing for cardiovascular indications. We are seeking a candidate with a keen interest to use routine healthcare data to validate drug repurposing hypotheses generated from in-house conducted genomics-based drug target prioritisation analyses. Specifically, we are looking to leverage data from Clinical Practice Research Datalink (CPRD) to conduct pharmacoepidemiology analyses using marginal structural (time-varying) models, including target trial emulation clone censor weighting. The appointee will join a multidisciplinary team that includes clinical and non-clinical epidemiologists, computational geneticists, statisticians, and data scientists. The successful appointee will conduct original research leading to publications.

This post is for an early career researcher with an exceptional research track record for their career stage. The appointee should hold a PhD, or have submitted by the time the post starts. They should have relevant experience with electronic healthcare records, be familiar with disease and medication terminology, and should have an applied understanding of causal inference using non-randomised data. Familiarity with causal inference methods employed in genetic epidemiology is highly desirable. You will be self-motivated, resourceful, 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.