Cornell University Ithaca, NY
Title: Postdoctoral Associate for Statistical Genetics and Genomics in Oat, Section of Plant Breeding and Genetics, School of Integrative Plant Science, CALS, Cornell University
A postdoctoral associate position is available to work in the area of statistical genetics and genomics in the Plant Breeding and Genetics Section at Cornell University. The position will be part of a multi-lab collaborative effort to improve the nutritional quality of oat through genomics-assisted breeding. This position involves the application of RNA-Seq for identifying eQTLs related to quantitative variation for metabolites in oat grain. In addition, whole-genome prediction approaches that combine genotypic and transcriptomic data will be developed and applied for the prediction of metabolomic and agronomic phenotypes. The ideal candidate will have expertise in statistical genetics, genomics, and programming. Responsibilities will include independent research in the analysis of next generation sequencing data, complex trait dissection and prediction, and training scientists and students. The position will involve close collaboration with a dynamic team of plant breeders, geneticists, and computational biologists.
A Ph.D. in plant breeding, genetics, physiology or related discipline with extensive training in molecular biology and statistical genetics methods. Programming skills (R/Java/Python) and working knowledge of RNA-Seq analysis, genome-wide association studies, and whole-genome prediction approaches. Excellent interpersonal and communication skills with a strong publication record.
A record of publication in the field of plant genetics and genomics. Knowledge of plant breeding, genetics and physiology practices. Experience with the manipulation and analysis of highly dimensional data sets from polyploid plants.
The position will include some supervision of undergraduate students involved in research on the project.
Anticipated Division of Time
- Studying the genetic basis of differential gene expression in oat grain40%
- Developing and implementing statistical genetics approaches to integrate genotypic, transcriptomic data sets for prediction of metabolomic and agronomic phenotypes40%
- Participation in preparation of annual reports and publications10%
- Formal and informal training of lab members and collaborators in statistical genetics and genomics10%
How to Apply
- A letter of interest in the position, C.V., and contact information for three references should be emailed to Michael Gore at: [email protected]
- Review of applications will begin immediately and continue until the position is filled.
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