- Entry level
- No Education
- Salary to negotiate
We are seeking a Research Associate in Molecular Epidemiology to work on the understanding causes of chronic diseases theme of the Heath Data Research UK.
The position is funded by Health Data Research UK which is the new national institute for data science for health, which was established in 2018 with long term funding support from research councils, UKRI, charitable and governmental research funders. HDR UK seeks to drive improvements in the health of patients and populations through research at regional and national scale. The triple mission of HDR UK spans discovery of disease mechanisms in science through:
- Precision medicine and trials to public health
- Establishing platforms and underlying infrastructure to enable research at national scale
- Developing training and capacity opportunities. To deliver this mission, the five major London universities – UCL (coordinating), Imperial College London, King’s College London, London School of Hygiene and Tropical Medicine and Queen Mary University of London – came together as a pan London Site. The terms of this partnership are set out in the Site Agreement. The six HDR UK Sites include London, Cambridge University (the Sanger and European Bioinformatics Institute), Oxford, the Midlands, Scotland and Wales/ Northern Ireland.
Duties and responsibilities
You will be expected to deliver collaborations across multiple sites in the UK to advance nationally prioritised projects. You are required to list HDR UK author affiliation and acknowledge HDR UK as a funder in all publications and presentations.
The successful candidate will study genetic and metabolic determinants in relation to chronic diseases in large well-established population cohorts from UK, USA and Europe. The analysis will leverage high resolution metabolomic data available in blood and urine and other state of the art omic analyses. Methodologies include a range of methods from simple regression models to multivariate approaches and various data reduction approaches such as Orthogonal Partial Least Squares regression (O-PLS), and deal with the high degree of autocorrelation within the data. Multiple testing and combining data across several studies are other challenges that should be addressed in the analysis. Genetic epidemiology methods (e.g. GWAS) and Mendelian Randomisation methodologies will also be used.
You will have a background in molecular epidemiology or biostatistics, with analytical and interpretative skills in omics data. Candidates will be interested in gaining/sharing knowledge and experience within and outside their domains.
Candidates who have not yet been officially awarded their PhD will be appointed as Research Assistant within the salary range £35,477 - £38,566 per annum.
The post is full time and fixed-term, for 36 months.
Interviews will take place the week commencing 03/02/2020.
For further information and an informal discussion contact Dr Elizabeth Hayes (email@example.com), for a formal discussion please contact Professor Paul Elliott firstname.lastname@example.org)
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