Research Fellow Full-time NEW

Research Fellow

The successful candidate will join the ECHILD team within the Child Health Informatics Group (CHIG) at the UCL Great Ormond Street Institute of Child Health, contributing to a programme of research using linked population-level health, education and social care data. ECHILD comprises records for approximately 20 million children and young people in England, including linked mother-child data, providing a unique resource for research into child health, development, healthcare utilisation, health inequalities and life-course outcomes. The post is strategically aligned with HDR UK's Driver Programmes in Social and Environmental Determinants of Health and Molecules to Health Records. Working closely with multidisciplinary colleagues across UCL and partner organisations, the postholder will contribute to the design, conduct and dissemination of high-quality research using large-scale administrative datasets and electronic health records. Research activities will span areas including child health, population health, developmental trajectories, health services research, population genomics and precision medicine. This role offers an excellent opportunity to contribute to methodologically rigorous and policy-relevant research within a highly collaborative environment. The successful candidate will apply and develop quantitative methods, contribute to scientific publications and research funding applications, and support the wider development of child health data science and population health research across UCL, ECHILD and HDR UK.

Key requirements: Experience/qualifications in the following: • PhD in epidemiology, biostatistics, health data science, public health, population health, or equivalent experience • Experience of conducting quantitative research using large-scale healthcare, administrative and/or electronic health record datasets, including the management and analysis of complex linked data • Strong understanding of epidemiological study design and statistical methods for longitudinal population health research • Knowledge of data governance, confidentiality and information security requirements for sensitive data Required skills: • Excellent statistical programming skills (e.g. R, Python or Stata) • Ability to contribute to the development of research questions and deliver high-quality research collaboratively within multidisciplinary teams • Ability to apply advanced analytical approaches, such as causal inference methods • Ability to work independently and manage competing priorities • Ability to conduct high-quality research and produce publications

What we offer: As well as the exciting opportunities this role presents we also offer some great benefits some of which are below: 41 Days holiday (including 27 days annual leave 8 bank holiday and 6 closure days) Defined benefit career average revalued earnings pension scheme (CARE) Cycle to work scheme and season ticket loan On-Site nursery On-site gym Enhanced maternity, paternity and adoption pay Employee assistance programme: Staff Support Service Discounted medical insurance