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BACKGROUND
The Barley CAP is a ground-breaking effort to apply association genetics to crop improvement in US elite barley germplasm. The data being created by this project is characterized by deep pedigrees, extensive marker data, population structure, inbreeding, and unbalanced design. To evaluate this data, we are assembling and adapting methods from plant, human and livestock genetics. These methods include imputation-based association mapping, genomic selection, and GxE analysis. The environment at Cornell includes nationally recognized research programs in population genetics, genomics and plant breeding, which will provide additional resources and stimulation.RESPONSIBILITIES
Incumbents will work in the labs of Jean-Luc Jannink and Peter Bradbury on efforts to
• Identify and make use of haplotypes in SNP data from barley inbreds, representative of North American elite and breeding pools.
• Determine optimal QTL detection methods involving single-locus or haplotype methods
• Scale-up genomic selection methods to datasets involving thousands of lines and markers
• Apply data to the elucidation of the demographic and evolutionary history of elite barleyREQUIREMENTS
Applicants should have a Ph.D. in quantitative, population, or computational genetics; knowledge of plant breeding; proven written and spoken communication skills.PREFERENCES
US citizens or Green Card holders are also preferred (others may apply but initial employment will be delayed).TERMS
Positions are for two years, extendible up to four. Earliest start date is 25 November 2007.LOCALE
USDA-ARS lab at Cornell University, Ithaca, New York, USACOMPENSATION
An excellent postdoctoral salary will be offered.HOW TO APPLY
A letter of interest in the position, C.V., and contact information for three references should be emailed to Jean-Luc Jannink and Peter Bradbury at:
JeanLuc.Jannink[at]ars.usda.gov
Peter.Bradbury[at]ars.usda.govDEADLINE
The positions will remain open until good candidates are identified.
Discussion forums: Opportunities: Two Postdocs in Quantitative / Statistical / Computational Genetics at Cornell--Ithaca, NY (US)
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