Cornell University, School of Integrative Plant Science – Section of Plant Breeding and Genetics

Position ID:Cornell-School of Integrative Plant Science – Section of Plant Breeding and Genetics-RA [#14352, WDR-00020445]
Position Title: Research Associate Position in Statistical Genetics of Sugar Kelp Improvement
Position Type:Other
Position Location:Ithaca, New York 14853, United States [map]
Subject Areas: Genetics / Statistical, Sugar Kelp
Appl Deadline:2019/10/31 (posted 2019/08/27, listed until 2019/10/31)
Position Description:    

Research Associate Position in Statistical Genetics of Sugar Kelp Improvement
Section of Plant Breeding and Genetics
School of Integrative Plant Science
College of Agriculture and Life Sciences
Cornell University



The position is in the lab of Jean-Luc Jannink, Section of Plant Breeding and Genetics at Cornell, and is part of a large ARPA-E grant to develop open-ocean grown sugar kelp (Saccharina latissima). Saccharina latissima is a brown algae or kelp. It is phylogenetically distant from both plants and animals, having diverged from green algae early in the evolution of eukaryotes. The project will explore its genome, the population history of sugar kelp globally, and take advantage of its biphasic lifecycle to rapidly domesticate it using cutting edge genomic selection methods.

The Section of Plant Breeding & Genetics, within the School of Integrative Plant Sciences, trains interdisciplinary scientists in the elaboration of new breeding methods, the discovery of genetic mechanisms important for economically important traits, and the development of genetic stocks, germplasm, and varieties. Cornell University plant breeders are world leaders in innovative plant breeding research, teaching, and extension, and we collaborate globally. The Jannink lab works with several crop species (wheat, oat, barley, cassava, and kelp) to develop new genomic prediction methods and integrate them optimally within breeding schemes. Many researchers are active in this area. We work together to discover, build on, and share new ideas and tools from across computational disciplines that lead to successful applied breeding outcomes.

The research associate (RA) will collaborate with scientists at the Woods Hole Oceanographic Institute, the University of Connecticut, and the HudsonAlpha Institute for Biotechnology. We are a team discovering together how to address a range of challenges from evaluating many unique genotypes in common gardens, to isolating high molecular weight DNA in kelp, to designing breeding schemes around the kelp life cycle. Primary tasks for the RA include the bioinformatic analysis of a large panel of resequenced haploid kelp gametophytes to identify variants, use the panel as an imputation reference population, and estimate important population genetic parameters of New England sugar kelp. Individuals from this panel have been mated and their sporophyte progeny are being evaluated off the Massachusetts and New Hampshire coasts by collaborators. The RA will be the team's expert resource on bioinformatics and quantitative genetic questions. The RA will analyze data from experiments for genome wide association between variants and multiple phenotypes, for the training of genomic prediction models, and for estimating parameters of kelp population and quantitative genetics. Based on these analyses, the RA will select among newly-generated gametophytes genotyped by low-depth skim sequencing. Finally, the RA will design and analyze validation field experiments measuring the performance of progeny sporophytes. Further possibilities for the data include research on linear models to predict heterosis and the identification of evolutionary conservation and signatures of selection in the sugar kelp genome.

Term is one year, renewable for an additional year contingent on performance and continued funding.

Anticipated Division of Time
  • Experimental and breeding program design and data analysis 60%
  • Communication and coordination with collaborators 20%
  • Preparation of quarterly reports to ARPA-E 10% Training of lab members and collaborators in statistical genetics and genomics 10%

Position Requirements
Ph.D. in statistical, population or quantitative genetics with experience or interest breeding applications, or Ph.D. in plant or animal breeding with emphasis on genomics, or population and quantitative genetics AND previous experience as a postdoc conducting genomic breeding. Ability to independently guide a teams of researchers conducting phenotypic analyses and performing crosses among kelp accessions.

Preferred Specific Skills
Sequence alignment and variant calling methods. Variant imputation methods. Genome-wide association studies and genomic prediction methods. High-dimensional data analysis. Basic notions of mating designs in breeding. Optimization and experimental design for field studies. Analysis of multi-generation breeding experiments. Quantitative genetic analysis of trials, estimation of inbreeding depression and variance components. Proven scientific writing ability and communication skills.

How to Apply
Candidates should send a statement of interest, curriculum vitae, contact information for three references, and a statement of diversity, equity, and inclusion. Applicants should submit all application materials via the website https://academicjobsonline.org/ajo/jobs/14352. Questions about the position can be addressed to Dr. Kelly Robbins at: krr73@cornell.edu. Review of applications will begin immediately and continue until the position is filled.


Diversity and Inclusion are a part of Cornell University’s heritage. We are a recognized employer and educator valuing AA/EEO, Protected Veterans, and Individuals with Disabilities.

Application Materials Required:
Submit the following items online at this website to complete your application:
And anything else requested in the position description.

Further Info:
www.cornell.edu
email
607-255-8819
 
Section of Plant Breeding and Genetics
School of Integrative Plant Science
College of Agriculture and Life Sciences
Cornell University
Ithaca, NY 14853

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