ACAD107863

We are looking for an enthusiastic researcher with strong quantitative skills to work on a Wellcome-funded project that seeks to understand the causal social, psychological, and biological mechanisms driving the impact of childhood adversity on anxiety., The successful candidate will join Professor Laura Howe's interdisciplinary research group in Population Health Sciences, Bristol Medical School, and will be a member of the MRC Integrative Epidemiology Unit - a leading centre for causal inference epidemiology. Professor Howe leads a group focused on making the best use of observational epidemiological data to understand the causal processes through which social factors influence health across the life course. The post-holder will also work closely with project partners from multiple UK and international institutions, and will support the meaningful involvement of people with lived experience in the research.

What will you be doing?

The successful candidate will conduct statistical analysis of data from prospective longitudinal cohort studies from the UK and Brazil, as well as large international biobanks, and will write up results for academic and non-academic dissemination. The project presents an excellent opportunity to use state-of-the-art statistical methodologies, including methods for dealing with missing data, longitudinal data techniques, and methods for enhancing causal inference (Mendelian randomization, genomic structural equation modelling, difference in difference, cross lagged panel models). The successful candidate will join a vibrant research team with diverse expertise, and opportunities for both formal and informal training to expand their research skills. The successful candidate will be expected to contribute to the project team as appropriate, e.g. by leading some analyses and papers as first author and contributing analysis to others as part of a team science model, by providing methodological
advice and training to project partners, and by supporting patient and public involvement and engagement.

This role would suit a researcher with a strong quantitative background (for example in epidemiology, applied statistics, or a related quantitative discipline) who is experienced in using Stata or R, and has experience of writing-up results as academic papers. Ideally, the researcher will have experience of analysing longitudinal cohort data and/or statistical methods for improving causal inference from observational data., A PhD (or working towards) or relevant professional/research experience in epidemiology, statistics, or a related quantitative discipline is essential. We are seeking someone with advanced quantitative skills, experience of analysing large, complex epidemiological data sets, and excellent written and oral communication skills.