Research Fellow

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

About us

Our mission is to maximise and advocate for the holistic health of all children, young people and the adults they will become, through world-class research, education and public engagement. The UCL GOS ICH, together with its clinical partner Great Ormond Street Hospital for Children, forms the largest concentration of children's health research outside North America. The 2024-29 GOS ICH strategy focuses on its five scientific programmes. GOS ICH's activities include active engagement with children and families, to ensure that our work is relevant and appropriate to their needs. GOS ICH generates the funding for our research by setting out our proposals in high quality applications to public, charitable and industrial funding bodies and disseminates the results of our research by publication in the medical and scientific literature, to clinicians, policy makers and the wider public. The Institute offers world-class education and training across a wide range of teaching and life learning programmes which address the needs of students and professional groups who are interested in and undertaking work relevant to child health. GOS ICH holds an Athena SWAN Charter Gold Award. Please only attach relevant documents to your application (qualifications, cover letters, supporting statements) and avoid attaching large files e.g. research papers, thesis, publications etc.

About the role

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. Experience with one or more of the administrative databases within ECHILD and/or UK primary care data would be an advantage. This role is eligible for hybrid working with a minimum of 40% (two days a week) on site. We will consider applications to work on a part-time, flexible and job share basis wherever possible. This post is funded for 18 months in the first instance. 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

About you

You will hold a PhD in epidemiology, biostatistics, health data science, public health, population health, or a related discipline (or have equivalent experience), with a strong track record of conducting quantitative research using large-scale healthcare, administrative and/or electronic health record data. You will have experience managing and analysing complex longitudinal datasets and a sound understanding of epidemiological study design and advanced statistical methods. You will be proficient in statistical programming using tools such as R, Python or Stata, and committed to high standards of reproducible and open research. We are seeking a collaborative and intellectually ambitious researcher with an interest in using population-scale data to address important questions in child health, population health and precision medicine. You will be able to contribute to the development of research questions, apply advanced analytical approaches, and communicate findings through high-quality publications and presentations. Experience of working with linked health and administrative datasets is essential. An interest in integrating genomic and molecular data with routinely collected healthcare and administrative records to advance precision medicine and precision public health would be particularly welcomed. Above all, you will be a highly motivated and organised individual who can work effectively both independently and as part of a multidisciplinary team, while embodying UCL's Ways of Working and commitment to sustainability.

Our commitment to Equality, Diversity and Inclusion

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. You can