JOHN INNES CENTRE

STATISTICAL EXPERIMENT ANALYST

DESCRIPTION

Applications are invited for a Statistical Experiment Analyst within the Computational Biology Group at the John Innes Centre. JIC is an internationally premier academic institute for basic and strategic research into the functioning of plants and microorganisms (http:/www.jic.bbsrc.ac.uk/corporate/science).

REQUIREMENTS

The postholder will be required to provide statistical and computational advice and support to JIC scientists on the design, analysis and interpretation of high-throughput experiments associated with our research, ideally for microarrays and subsequently also for metabolomics and proteomics projects; the successful candidate will have the background and flexibility necessary for them to acquire a detailed knowledge of these fields and will receive any training required.

Candidates should have an MSc or equivalent in statistics plus at least one year?s experience in the design, analysis and interpretation of biological experiments. Excellent communication skills, with experience as a consultant, in order to support, advise and direct students, post-doctoral and senior scientists is essential. The ideal candidate will be familiar with genetics, genomics and molecular biology.

Salary on appointment will be within the range £26,000 to £30,500 per annum, plus a retention and recruitment allowance (currently up to £4,000 per annum), depending on qualifications and experience. JIC offers a choice of a final salary and stakeholder pensions.

HOW TO APPLY

Please contact David.Lowe[at]bbsrc.ac.uk for information on applications. Application forms can be obtained by writing to the Personnel Officer, John Innes Centre, Norwich Research Park, Colney, Norwich, Norfolk, NR4 7UH, or from our web site http://www.jic.bbsrc.ac.uk/corporate/Vacancies/Vacancies.htm please quote reference number 12 51 on all correspondence. The closing date for completed application forms will be 23rd January 2004.


The John Innes Centre is a registered charity (No223852) grant-aided by the Biotechnology and Biological Sciences Research Council and is an Equal Opportunities Employer.