Research Associate in Statistical Genetics and Bioinformatics

University College London - UCL - Division of Biosciences / Research Department of Genetics, Evolution and Environment

We are seeking a talented postdoctoral biostatistician/statistical geneticist to investigate the genetic architecture of obesity and diabetes in animal models of these important human diseases. The principal duties involve the statistical genetic analysis of data arising from a study of obesity and diabetes in a population of outbred heterogeneous stock (HS) rats. The data comprise over 20 obesity and diabetes traits, transcriptome data from liver and adipose tissue and genome-wide genotype information collected in these animals. The analysis will use statistical genetic methods, previously developed by our group (Mott et al 2000 PNAS, Yalcin et al 2005 Genetics, Durrant and Mott 2011 Genetics) and others (eg Gatti et al 2014) to find regions of the genome that affect outcomes related to diabetes and obesity. Specifically, this person will identify quantitative trait loci (QTL) for both phenotypic and transcriptome data in order to determine the gene networks which correlate with disease.

This NIH-funded project is a collaboration between Richard Mott at University College London (UCL) (see ) and Dr. Leah Solberg Woods at the Wake Forest School of Health, North Carolina USA. The post-holder will join Richard Mott’s group at UCL, a dynamic group working on quantitative and population genetics across a wide range of animal and plant species.

The group is affiliated to the Department of Genetics, Evolution and Environment (GEE) and the UCL Genetics Institute (UGI), a a vibrant centre of excellence in medical, statistical and computational genetics, offering one of the most exciting work environments in the UK. GEE is a large and collegial Department, which embraces essentially all aspects of modern biology and has grown significantly over recent years.

The post is funded for 2.5 years in the first instance.

The successful applicant should have relevant scientific education (PhD degree in Biostatistics, Computational Biology, Statistical Genetics or related field), preferably with a publication track record. Knowledge of applied statistics using R and programming experience is necessary, as well as good written and oral communication skills. Appointment at Grade 7 is dependent upon having been awarded a PhD. Or if about to submit a PhD, the appointment will be at Grade 6B (£29,809- £31,432 per annum, inclusive of London Allowance) with payment at Grade 7 being backdated to the date of final submission of the PhD thesis.

UCL vacancy reference: 1590225.

Applicants should apply online. To access further details about the position and how to apply please click on the ‘Apply’ button below.

If you have any queries regarding the application process please contact Scott Boyne on quoting the reference number 1590225 in the subject line.

If you have any queries regarding the vacancy, please contact Professor Richard Mott on

Closing Date: 11 November 2016.
Latest time for the submission of applications: 23:59.
Interview Date: TBC.

UCL Taking Action for Equality

This position does not meet the resident labour market test under UK Border Agency rules and therefore UCL would be unable to obtain the right to work for non-EEA nationals whose employment would require a Tier 2 visa.

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