Research Associate in Computational Epidemiology / Statistics / Modelling

Imperial College London - Department of Epidemiology and Biostatistics

We have an exciting opportunity for a Research Associate in Computational Epidemiology and Applied Statistics to contribute to a pioneering project on the analyses of methylation, gene expression, and genetic data in order to explore molecular mechanisms triggered by exposure to tobacco smoke and affecting the risk of lung cancer.

‘Mechanomics’ is a CR-UK funded project which compiles a unique multi-omic dataset including high-resolution genotype data (in N>45,000 individuals), >2,600 individuals in which (blood-derived) DNA methylation profiles are also available. From more than 750 of these individuals, genome-wide gene expression profiles (mRNA) are available or will be generated during the project (N=400). Mechanomics project is led at the Department of Epidemiology and Biostatistics, Imperial College London, but also involves international partners from world leading institutions in cancer epidemiology, applied statistics, and molecular epidemiology: the University of Utrecht (the Netherlands), the Arctic University of Tromso (Norway), the International Agency for Research on Cancer (IARC, France),  Maastricht University (the Netherlands), Queensland University of Technology (Australia), Dartmouth University (USA), and the Lunenfeld-Tanenbaum Research Institute at Mount Sinai Hospital (Canada). The project is actively linked to two large lung cancer consortia ILCCO and TRICL.

The post holder will develop and apply (in tight links with all the project partners) novel statistical models first to perform in-depth analysis of existing methylation and gene expression data in relation to both exposure to tobacco smoke and to future risk of lung cancer. Computational approaches will also aim at enabling the data integration across both platforms. In addition, disease progression models (compartmental models) will be developed and will include (pre-selected) genetic variants in order to identify their functional role in the development of lung carcinogenesis.

The successful applicant will have a PhD in Epidemiology, Biostatistics or related quantitative discipline or equivalent. A sound understanding of epidemiological concepts particularly in relation to molecular epidemiology and strong methodological skills, including experience in analysing large-scale and high dimensional data, disease modelling and programming are essential.

This post is full time for a fixed term of 24 months in the first instance and will be based at the St Mary’s campus, Paddington.

For informal discussions please contact Dr Chadeau-Hyam (m.chadeau@imperial.ac.uk).

Our preferred method of application is online via our website at http://www3.imperial.ac.uk/employment (please select “Job Search” then enter the job title or vacancy reference number into “Keywords”). Please complete and upload an application form as directed quoting reference number SM256-16AL.

Alternatively, if you are unable to apply online, please email adrian.lacey@imperial.ac.uk to request an application form.

Closing Date: 15 December 2016 (Midnight GMT)

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