Research Associate/Senior Research Associate in Population Genetics and Epidemiology
The Integrative Epidemiology Unit at the University of Bristol are seeking to recruit a talented individual for 1 year to develop causal inference tools for epidemiology using Bayesian or other advanced statistical methodology. The goal is to leverage recent advances in databases of Genome Wide Association Studies (GWAS) results, such as MR-Base (www.mrbase.org) to improve understanding of the causal structure between genes and phenotypes, and between exposures and phenotypes. The successful applicant will work with Dr Daniel Lawson in Population Health Sciences and the Department of Statistics.
This position involves the development of methodology for performing causal inference in genetics using instrumental variables via Mendelian Randomisation, incorporating additional information such as the known effects of genetic loci (via MR Base) and population structure. The developed methods can be applied either to readily available summary statistic data, or to large datasets such as the UK Biobank project. The details of the project can be fit to the applicant, varying the focus between application, mathematics, and simulation-based justifications. The post could suit a statistician with knowledge of Bayesian methodology, or an expert in causal inference, or a mathematically proficient geneticist or bioinformatician.
The MRC Integrative Epidemiology Unit at the University of Bristol is a world leading institute for the study of causality in epidemiology. It would be expected that the post-holder interact with experts across the Unit, ranging from methodology for robust inference, through graphical models of all causal relationships, to specific important applications.
The position is available for up to 12 months and runs until 30th September 2019. It is based in the Integrative Epidemiology Unit in the School of Social and Community Medicine, with optional links to the department of Statistics. It is funded through a Wellcome Trust and Royal Society research grant.
Name, email and number for informal contacts: Daniel Lawson, Dan.Lawson@bristol.ac.uk, 0117 331 3376
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