We have an exciting opportunity for a full-time Bioinformatician to join the research group of Professor Ken Smith in the Department of Medicine within the University of Cambridge.
Working within a world class and multi-disciplined research team the successful applicant will have the opportunity to undertake their own bioinformatic research projects in autoimmune disease genomics as well working collaboratively to provide analytical support for the group.
The Smith Laboratory is focused on understanding autoimmune and inflammatory disease and applying this knowledge to the clinical setting. We do this through the study of fundamental immunological mechanisms, enhanced by our exploitation of genetic and genomic data from well-characterised patient cohorts. This combined approach using human and animal data and state-of-the-art bioinformatic methodology, allows us to explore immunological mechanisms of relevance to human disease, and to translate our results into applications of direct benefit to patients. Example publications: McKinney et al Nature 30: 612-616, 2015: Lee et al Cell 155:57-69,2013; Lyons et al New Engl J Med 367:214-223,2012.
The role holder will have experience of using computational approaches to analyse diverse genomic datasets. Working within a Linux environment, they will apply this knowledge to data generated within the Smith research group (e.g. GWAS, RNA-Seq and clinical information), to characterise the molecular changes underlying autoimmune and inflammatory disease susceptibility and prognosis. This opportunity requires scripting ability (at least one of Perl, Python or Bash), familiarity with short read sequence data quality control and analysis, and relevant statistical understanding, preferably within the R environment. Additional duties will include providing ad hoc bioinformatics support and advice for researchers within the research group, as well as collaborative work with other groups in Medicine, the MRC Biostatistics Unit and others. Excellent organisational skills and the ability to work as part of a team, as well as independently, are also essential.
ixed-term: The funds for this post are available for 3 years in the first instance.
To apply online for this vacancy, please click on the 'Apply' button below. This will route you to the University's Web Recruitment System, where you will need to register an account (if you have not already) and log in before completing the online application form.
Please ensure that you upload a covering letter and CV in the Upload section of the online application. If you upload any additional documents which have not been requested, we will not be able to consider these as part of your application.
Please include details of your referees, including email address and phone number, one of which must be your most recent line manager.
Closing date for applications is 21st April 2017, with an interview date yet to be confirmed.
Please quote reference RC11698 on your application and in any correspondence about this vacancy.
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