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The Wellcome Trust Sanger Institute is a world leader in genomic research, with an expanding scientific programme dedicated to understanding gene function in health & disease.

We are looking for an enthusiastic and ambitious postdoctoral fellow (PDF) to join the metabolic disease group at the Wellcome Trust Sanger Institute. The role involves analysis of large datasets including GWAS data, whole-exome and whole-genome sequence data from various patient cohorts focusing on common metabolic disease (type 2 diabetes, obesity and underlying quantitative traits) as well as rare extreme disease phenotypes (severe insulin resistance and early onset obesity). Over the coming years the metabolic disease group will also be involved in building partnerships in Africa to study the genetics of diseases of relevance to its peoples and providing a further avenue available for project development. The ideal candidate will be able to develop and drive their own research ideas taking advantage of the resources available to the group, as well as work as part of a team.

Key responsibilities
• Managing and analysing GWAS data;
• Managing large-scale whole-genome and whole-exome datasets;
• Investigating genetic association of sequence-derived variants with phenotypes of interest;
• Develop and validate novel analytical methods where required;
• Design follow-up studies;
• Develop own research projects;
• Work in collaboration with the UK10k project team as well as with other analysts involved in large international collaborative projects;
• Present work at international meetings;
• Draft manuscripts for publication;
• Communicate with collaborators.

Essential Skills
We are looking for candidates with a strong record of academic achievement including a relevant degree. Good programming and statistical skills are essential as is experience of working with large-scale genetic data.
• Demonstrable experience and initiative in developing and leading projects;
• Extensive experience in quantitative science as evidenced for example by a postgraduate degree in a relevant subject (e.g. Statistics, Computing);
• Good scripting/programming skills;
• Firm grounding in statistical methods;
• Previous experience in working with large-scale (empirical and/or simulated) datasets;
• Experience in the application of statistical methods to the analysis of genetic data;
• Strong written and verbal communication skills

Ideal Skills
• Experience in managing and analysing whole genome sequence data
• Strong track record in preparing publications and other written materials
• Demonstrable good project management and organisational skills.
• Track record of developing new analytical approaches of genetic data

Other information
The metabolic disease group (http://www.sanger.ac.uk/research/projects/metabolicdisease/) is a multidisciplinary team that combines large-scale genetic and genomic approaches, and studies in model organisms to understand the aetiology of various metabolic diseases. The group is involved in many large international consortia such as MAGIC, GIANT and the recently launched Uk10k project (www.uk10k.org) and work is very collaborative with internal and external groups.

The role will be funded for 3 years although applicants will be encouraged to apply for their own fellowship.

Excellent facilities are available and there is a strong commitment to career development.

Postdoctoral Fellows are typically in their first or second postdoctoral position as part of a period of early career research training.

Successful applicant(s) who have submitted their PhD thesis and are awaiting their PhD award to be confirmed will be placed on a transitional pay point, currently £26103. On confirmation applicants will be moved on to the pay scale above

The closing date for this position is 22nd September 2011

Benefits
The Institute has excellent purpose built facilities on the Genome Campus, Hinxton on the outskirts of Cambridge. We offer a comprehensive range of benefits including a final salary pension scheme and excellent on-site facilities. Further details can be found on our website https://jobs.sanger.ac.uk,

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