Research Fellow

at  University College London

ABOUT US

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 statistical genetics, bioinformatics, and computational biology methods to organise, interpret, and apply data to support precision medicine. A key focus is accurate drug target identification and validation by integrating human genomics with evidence from electronic healthcare data and disease-specific biological annotations. 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 genetic epidemiology, methods development in Mendelian randomization, and health data science. UCL boasts a strong Computer Science Department and a number of local AI-focused tech start-ups with which our group collaborates

ABOUT YOU

This role will suit individuals with strong computational experience, coupled with an understanding of medicine and/or biology. The appointee should preferably hold a PhD or possess equivalent experience in medicine, biology, bioinformatics, health informatics, computer science, or data science. We are looking for evidence of research experience and proficiency in conducting quantitative analysis. Prior experience with scaled analysis on Unix-based systems is essential. Applied experience with (scaled) Mendelian randomisation is desirable, as is experience working with electrocardiogram or cardiac imaging data. You are motivated, resourceful, capable of working independently, and a collaborative team member. We place strong emphasis on supporting career development and encouraging independence. The post is available as a Grade 7 or Grade 8 post. Please see the job description for further details. If a PhD is not yet awarded at the start date, appointment will be at Research Assistant grade 6B £38,357 - £41,005 per annum (including London Allowance), with payment at grade 7 backdated to the date of submission of the final PhD thesis.

Atrial fibrillation (AF) is an arrhythmia of the upper chambers of the heart (the atria) characterized by a loss of organized contraction. People may develop AF for a variety of reasons, and AF itself can lead to sudden cardiac death, progressive heart failure, stroke, early cognitive decline, and dementia. Treatment for AF is limited and primarily focused on rhythm control and stroke prevention, with most drugs not addressing the underlying disease substrate. The primary goal of this position is to identify and prioritize novel and repurposed drug targets for AF and related cardiac conditions. The successful applicant will have access to large genetically linked population biobanks (UK Biobank, All of Us, Our Future Health), nationwide prescription data (GPRD), and in-house bioinformatics tools covering proteomics, tissue/cell expression profiles, and clinical trial evidence. The successful candidate will be supported in building a research profile in computational analysis of genomics and health records, while also developing advanced coding skills to publish and maintain computational tools for the broader scientific community.