Senior Research Associate in Statistics / Epidemiology

United Kingdom
£38,017 - £42,792
Jan 02, 2021
Feb 01, 2021
Organization Type
University and College
Full Time
The role

We have an exciting opportunity for a talented postdoctoral researcher to join the MRC Integrative Epidemiology unit (MRC IEU) at the University of Bristol to work on a variety of research projects, including COVID-19 related research using population based data with a focus on combined geographical and time series analyses. A particular focus will be to consider how issues of selection (e.g. for receiving a COVID-19 test) will influence the data available for such analyses, and to formulate ways of addressing this

The post will build on our recent work using Mendelian randomization to identify influences on participation in studies, and development of methods to overcome sources of bias in case-only studies and studies using non-random samples. You will take a lead role in applying novel methodologies for genome-wide association and Mendelian randomization in the context of complex, time-varying phenotypes, and in samples which may not have been selected at random.

What will you be doing?

Analyse COVID-19 data, particularly using multilevel/time-series analyses and developing/applying methods to account for collider bias.
  • Clean and analyse data from large cohort studies and electronic health records
  • Write papers for peer reviewed journals, present work internally and at international conferences
  • Work with researchers from other programmes within the MRC IEU on the application and improvement of novel analytical methods to address selection bias in causal analyses
  • Prepare, annotate, and document datasets and projects for other researchers (meta-data, QC workflow summary and description of data)

You should apply if

an interest in the problems caused by selection in epidemiology, particularly in COVID-19 studies.
  • a strong background in applied statistics, epidemiology, statistical genetics, or other relevant quantitative discipline.
  • an understanding of analysis of geographical and time-trends in epidemiology
  • experience of applied statistical analysis using large datasets
  • an understanding of genetic association and Mendelian randomization approaches
  • proficiency in statistical and programming languages (e.g. R)
  • proficiency in UNIX-like platforms and high-performance computing

for informal enquires please contact: Kate Tilling,

We welcome applications from all members of our community and are particularly encouraging those from diverse groups, such as members of the LGBT+ and BAME communities, to join us.

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