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Research Assistant/Research Associate/Senior Research Associate* Research Assistant: £25,298 - £29,301 Research Associate: £29,301 - £38,183 Senior Research Associate*: £39,324 - £49,772 *NB: The status of Senior Research Associate is awarded on the basis of individual merit and may be awarded to the successful candidate if approved by the Faculty Board of the Cambridge School of Clinical Medicine We seek a talented and ambitious statistical geneticist to join a team of statistical geneticists, genetic epidemiologists and bioinformaticians working on large-scale genomic studies of cardiovascular disease in the Cardiovascular Epidemiology Unit (CEU), a research group of the Department of Public Health and Primary Care in University of Cambridge. The successful candidate will use genome-wide epidemiological, computational and statistical techniques to investigate potential molecular targets for the treatment of sickle cell anaemia, a debilitating hereditary haematological disorder. Sickle cell anaemia is caused by an abnormality of haemoglobin and affects approximately 10,000 people in the UK alone. The disorder can interrupt healthy blood flow, starving tissues of oxygen and causing severe pain. Presently there is no cure for sickle cell anaemia, but the up-regulation of foetal haemoglobin HbF, a protein with similar function to adult haemoglobin, which is expressed during foetal and infant development, is a therapeutic option. The appointee will work in the genetics team at the CEU, which has a track record of publishing high quality research. We have strong links to other groups in the University and surrounding research institutes including the genomics programmes of the MRC Biostatistics Unit, the Department of Haematology and the Wellcome Trust Sanger Institute. Indication of Key Duties: (this is not an exhaustive list) • Identify and evaluate existing statistical methods and, where appropriate, develop novel statistical or computational techniques to test hypotheses relevant to the research programme using genetic, cellular and multiomic data. e.g. genome-wide association analyses • Implement statistical analyses to test hypotheses of interest and perform such analyses using general purpose statistical software, genetic analysis software and, where necessary, bespoke programmes. • Work closely with colleagues to help interpret findings and draft manuscripts for publication and internal reports. Essential Skills: • A relevant post-graduate training, ideally in genetic epidemiology or applied statistics e.g. PhD in Statistics, Statistical Genetics, Medical Statistics, Genetic Epidemiology or Biostatistics, or equivalent experience. • A good understanding of inferential and statistical concepts and a broad range of relevant statistical techniques. Strong computational skills. • Experience of manipulating and managing large datasets. • Understanding of fundemental elemantary mechanisms of human genetics and molecular biology, at advanced secondary school level. e.g. inheritance, the central dogma of molecular biology. • An ability to communicate and present results to other statisticians, bioinformaticians, epidemiologists and scientists. The funds for these posts are available for 2 years from commencement in the first instance Appointment at research associate is dependent on having a PhD (or equivalent experience), including those who have submitted but not yet received their PhD. Where a PhD has yet to be awarded appointment will initially be made at research assistant and amended to research associate when the PhD is awarded. Location: Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Strangeways Research Laboratory, Worts Causeway, Cambridge, CB1 8RN (approx 2 miles south of city centre) Informal enquiries can be made to: Liza Clarke ([log in to unmask]) or telephone 01223 748622. Closing date: 12th March 2017 Interview Dates: Week commencing 20th March 2017 To apply online for this vacancy, please visit http://www.jobs.cam.ac.uk/job/12441/. This will route you to the University's Web Recruitment System, where you will need to register an account and / or log in before completing the online application form. (Previous applicants to this role need not apply) Please ensure that you upload a covering letter and CV in the Upload section of the online application. If you upload additional documents which have not been requested, we will not be able to consider these as part of your application. You may leave the list at any time by sending the command SIGNOFF allstat to [log in to unmask], leaving the subject line blank.