About us
The Centre for Longitudinal Studies is multidisciplinary research centre, and is funded by ESRC as a Resource Centre which leads four of Britain’s internationally renowned cohort studies:
- 1958 National Child Development Study (NCDS)
- 1970 British Cohort Study (BCS70)
- Millennium Cohort Study (MCS)
- Next Steps (formerly the Longitudinal Study of Young People in England)
About the role
CLS is looking to increase its statistical expertise by the appointment of a Research Fellow in Statistics/Quantitative Social Science. This post represents an exciting opportunity to work on the new Early Life Cohort Feasibility Study, contributing to the assessment of response, representativeness, and measurement quality in its first data collection.
The post will also help develop the applied statistical and survey methods research of the Centre, and in so doing undertake high-impact research in CLS’ longitudinal studies, including in NCDS, BCS70, MCS, and Next Steps and the other newer CLS cohorts (ELC-FS, COT2020s and COSMO) using rigorous quantitative methods.
You will lead and conduct high quality applied statistical methodological research. The main areas of research will include:
- i) Non-response and missing data: non-response analysis, response weight derivation and development/application of other approaches to the handling of missing data.
- ii) Measurement: assessing measurement properties of different measures and modes of data collection, including the assessment of data quality, mode effects and approaches to adjust for these.
iii) Causal inference: translational work to demonstrate the application of modern causal inference methods within the context of the CLS cohorts.
You will contribute to outputs including publications in peer-reviewed journals and to dissemination via national and international conferences. An important part of the role will be translating research outputs into highly accessible User Guides and training events providing detailed methodological toolkits and practical guidance for our users to apply in their own research.
This role will provide a fantastic opportunity for early career training. Candidates will be supported to continue their academic development (e.g. through Fellowship applications).
Optional teaching opportunities are available at undergraduate and postgraduate level.
UCL is currently trialling hybrid working and it may be possible for the successful applicant to work remotely for up to 60% of the week depending on their location and requirements of the role. This can be discussed during the recruitment process.
This post is available until 31st August 2025 in the first instance.
About you
You will have completed, or be near completion of your PhD in statistics, or a quantitative social science or health-related discipline.
You will also have experience of using statistical methods in relation to missing data, measurement issues and/or causal inference and expertise in statistical software such as Stata, R, and/or other relevant statistical software.
Your application form should address all the person specification points and should clearly demonstrate how your skills and experience meet each of the criteria.
It is important that the criteria are clearly numbered and that you provide a response to each one.