Postdoctoral Associate | Statistical Genetics of Cassava | Section of Plant Breeding and Genetics, CALS
Postdoctoral Associate in Statistical Genetics of Cassava
Section of Plant Breeding and Genetics
School of Integrative Plant Science
College of Agriculture and Life Sciences
Cornell University, Ithaca, New York
The position is in the lab of Dr. Jean-Luc Jannink, in the Section of Plant Breeding and Genetics at Cornell, within the NextGen Cassava project (www.nextgencassava.org). Cassava is a critical food security crop in sub-Saharan Africa for which genomic resources are now being rapidly developed. The NextGen Cassava project leverages those resources in a large, multinational effort to empower farmers through innovative, sustainable cassava breeding.
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 creation of genetic stocks, germplasm, and varieties. We promote a collaborative and interactive workspace to improve learning, cross connectivity, and mutual support between basic and applied researchers. 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 sugar 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. NextGen Cassava researchers at Cornell work with primary collaborators in Nigeria, Uganda, Tanzania and a wider network of collaborators at other research institutions. The hired person will join this team to implement quantitative genetic and genomic analyses and interact with collaborators across four continents. Applied research will include analysis of multi-environment trials run across programs to estimate covariances across environments to propose optimal networks of trialing sites. This network should be coordinated to breeding programs targeted geographies and product profiles. The candidate will also develop and apply methods to account for experimental error and genomic prediction accuracies to optimize breeding program resource allocation across population improvement and product development pipelines.
In addition to this applied breeding work, the postdoc will be encouraged to branch out and explore new methods, better implementation, or data acquisition to improve our team's analysis capacity overall. We encourage collaboration with experts at Cornell and elsewhere and will support intellectually and financially as feasible. Many possibilities for exploration range from breeding scheme simulation, to exploration of historical data in cassavabase, to leveraging information from low-depth sequencing of parents in African cassava breeding programs. We will develop research focus through discussion in the team and with collaborators whose work may be enhanced by research outcomes. There is tremendous scope within the lab for research that will have high impact on this important crop and on plant breeding in the genomics era generally.
NextGen Cassava operates in effect as a breeding company, with the candidate postdoc joining its "Research Division". The candidate will learn aspects of effective management and leadership. This experience should provide excellent preparation for a future career in industry or academia.
Extensive travel and teaching in sub-Saharan Africa (~6 weeks / year) will be required.
Term is one year renewable to three years contingent on performance.
Anticipated Division of Time
Multi-environment trial analysis to optimize resource allocation in cassava breeding -35%
Basic research to improve NextGen cassava team analysis capabilities -35%
Participation in preparation of annual reports and publications -10%
Formal and informal training of lab members and collaborators in statistical genetics and genomics -20%
Ph.D. in plant or animal breeding with emphasis on multivariate mixed linear models, genomics, bioinformatics; or Ph.D. in statistical or computational areas of genetics. Experience with high-dimensional data analysis; One or more programming languages; Proven scientific writing ability and communication skills.
Experience in plant breeding practice, analysis of plant breeding data, statistical genetics, and crop physiology; Knowledge of databases / database programming.
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Internal Number: JOB_POSTING-3-26492
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