Postdoctoral Research Associate in Quantitative Genomics

Contract Type: Fixed term for 2 years

Faculty: Faculty of Medicine, Dentistry and Health

Location: Sheffield Institute for Translational Neuroscience (SITraN)

Discovery of causative mechanisms for disease requires new approaches to exploit the digitally encoded information available in the growing repositories of high dimensional data for biomedical research. You will work closely with our multidisciplinary research group to develop, apply and validate novel methods for interpretation of drug induced response signatures using bioinformatics-based approaches. This innovative opportunity will exploit your skills in quantitative biology, showcasing your ability to develop methods that have high impact and provide clinical and wet lab applications. You understand the need for translation and are a highly independent researcher who wants to exploit your interest in rapid predictive approaches to drug discovery. This is a career launching post and comes at a time when the skills you will acquire will be in high demand in both academics and industry.

Working in a stimulating environment in close association with industry, clinical and wet lab scientists, you will join a growing team in the Centre for Genome Translation working across Sheffield University’s Institute for Translational Neuroscience in the department of Neuroscience and also the department of computer sciences. You will work with datasets generated at Harvard, Sheffield and across our global consortia to exploit signatures derived from whole genome human variation data, gene expression, drug response, and high throughput data from the LINCS project ( the NIH Advanced Medicines Partnership (, and our local teams.

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You will be trained and travel to local and international meetings, and you will collaborate closely with the groups at Biogen in Cambridge, USA and Sheffield departments of Computer Sciences and Neuroscience as well as Sheffield Hospital.

Applicants should have a high calibre PhD (or equivalent qualification) in an area such as computational biology, biomedical research, genomics, computer science, mathematics, biostatistics, systems biology or combination of these. Applicants will also need to have a strong biological background and be skilled in scripting with demonstrable understanding of working together with biomedical researchers and quantitative computational biologists. Confidence in quantitative aspects of data manipulation is essential.

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