Job Description:
An exciting opportunity has arisen for a highly-motivated and talented Bioinformatician/Statistical Geneticist to join a research group based in the new Big Data Institute, focusing on pharmacogenomic and genetic epidemiological studies of cardiovascular disease and its treatments. The research programme makes use of ‘big data’ resources in order to discover and undertake in-depth explorations of genomic predictors for vascular disease, its risk factors, and patient response to cardiovascular therapies. The very large-scale data that are emerging provide the opportunity to work with a wealth of newly generated genome-wide data from state-of-the-art arrays as well as with imaging, sequence and epigenetic data. You will have bioinformatic/statistical genetic/genetic epidemiological expertise and relevant experience of working on human genetic studies. The post will involve bioinformatic processing and analyses of a range of genomic data as well as tackling new genomic chall enges for population health. You will have a PhD (or MSc plus subsequent relevant experience) in a numerate or computational discipline, relevant experience of processing, manipulating, analysing and interpreting human genomic data and experience using programming languages and statistical packages. Excellent organisational and communication skills are also essential.
Additional Info:
The Nuffield Department of Population Health (NDPH) contains world-renowned population health research groups. This post provides an excellent opportunity for training and development of expertise in medical statistics and statistical programming within a leading multi-disciplinary academic unit with an unrivalled reputation for promoting the use of ‘big data’ to reliably identify findings important to population health. The post is full-time (part-time considered) and is fixed-term for 3 years in the first instance. The closing date for applications is 12.00 noon on Monday 2 October 2017. https://www.recruit.ox.ac.uk/pls/hrisliverecruit/erq_jobspec_version_4.jobspec?p_id=130268[Click Here to Access the Original Job Post]
An exciting opportunity has arisen for a highly-motivated and talented Bioinformatician/Statistical Geneticist to join a research group based in the new Big Data Institute, focusing on pharmacogenomic and genetic epidemiological studies of cardiovascular disease and its treatments. The research programme makes use of ‘big data’ resources in order to discover and undertake in-depth explorations of genomic predictors for vascular disease, its risk factors, and patient response to cardiovascular therapies. The very large-scale data that are emerging provide the opportunity to work with a wealth of newly generated genome-wide data from state-of-the-art arrays as well as with imaging, sequence and epigenetic data. You will have bioinformatic/statistical genetic/genetic epidemiological expertise and relevant experience of working on human genetic studies. The post will involve bioinformatic processing and analyses of a range of genomic data as well as tackling new genomic chall enges for population health. You will have a PhD (or MSc plus subsequent relevant experience) in a numerate or computational discipline, relevant experience of processing, manipulating, analysing and interpreting human genomic data and experience using programming languages and statistical packages. Excellent organisational and communication skills are also essential.
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Additional Info:
The Nuffield Department of Population Health (NDPH) contains world-renowned population health research groups. This post provides an excellent opportunity for training and development of expertise in medical statistics and statistical programming within a leading multi-disciplinary academic unit with an unrivalled reputation for promoting the use of ‘big data’ to reliably identify findings important to population health. The post is full-time (part-time considered) and is fixed-term for 3 years in the first instance. The closing date for applications is 12.00 noon on Monday 2 October 2017. https://www.recruit.ox.ac.uk/pls/hrisliverecruit/erq_jobspec_version_4.jobspec?p_id=130268[Click Here to Access the Original Job Post]