ARS Office/Lab and Location: A postdoctoral research opportunity is available with the U.S. Department of Agriculture (USDA), Agricultural Research Service (ARS), Animal Genomics and Improvement Laboratory (AGIL) Unit, located in Beltsville, Maryland.
The Agricultural Research Service (ARS) is the U.S. Department of Agriculture’s chief scientific in-house research agency with a mission to find solutions to agricultural problems that affect Americans every day from field to table. ARS will deliver cutting-edge, scientific tools and innovative solutions for American farmers, producers, industry, and communities to support the nourishment and well-being of all people; sustain our nation’s agroecosystems and natural resources, and ensure the economic competitiveness and excellence of our agriculture. The vision of the agency is to provide global leadership in agricultural discoveries through scientific excellence.
Research Project: This research opportunity will be using the National Cooperator Database which is managed by Council on Dairy Cattle Breeding (CDCB) that is shared with AGIL researchers. Under the guidance of a mentor, the participant will gain experience in discovering and developing improved methods for the genetic and genomic evaluation of economically important traits of dairy cattle to conduct fundamental genomics-based research aimed at improving health and productive efficiency. The participant will collaborate with scientists and support staff to generate research results for use by all segments of the dairy industry as well as dairy producers across the nation and globe. This appointment will also include opportunities to contribute to the basic and applied genetics and genomics research and tool development for dairy cattle resulting in peer-reviewed publications.
Learning Objectives: Throughout this research project, the participant will gain experience developing and using pipelines for research studies including genetics, genomics, statistics, bioinformatics, and computational strategies used to associate animal phenotypes with genotypes for predicting merit of future animals.
Mentor(s): The mentor for this opportunity is Paul VanRaden (Paul.VanRaden@usda.gov). If you have questions about the nature of the research please contact the mentor(s).
Anticipated Appointment Start Date: Fall 2022. Start date is flexible and will depend on a variety of factors.
Appointment Length: The appointment will initially be for one year, but may be renewed upon recommendation of ARS and is contingent on the availability of funds.
Level of Participation: The appointment is full-time.
Participant Stipend: The participant will receive a monthly stipend commensurate with educational level and experience.
Citizenship Requirements: This opportunity is available to U.S. citizens, Lawful Permanent Residents (LPR), and foreign nationals. Non-U.S. citizen applicants should refer to the Guidelines for Non-U.S. Citizens Details page of the program website for information about the valid immigration statuses that are acceptable for program participation.
ORISE Information: This program, administered by ORAU through its contract with the U.S. Department of Energy (DOE) to manage the Oak Ridge Institute for Science and Education (ORISE), was established through an interagency agreement between DOE and ARS. Participants do not become employees of USDA, ARS, DOE or the program administrator, and there are no employment-related benefits. Proof of health insurance is required for participation in this program. Health insurance can be obtained through ORISE.
Questions: Please visit our Program Website. After reading, if you have additional questions about the application process please email USDA-ARS@orau.org and include the reference code for this opportunity.
Preferred Skills:
– Ph.D. in quantitative and computational sciences or related fields such as Population Genetics, Quantitative Genetics, Bioinformatics, or Animal Breeding
– Experience working with genetics and genomic data
– Experience Scripting in Python or R for data processing
– Experience handling data analysis and visualization
– Experience working with large, diverse datasets and data-mining approaches
– Experience with relational databases
– Experience installing and running complex software programs using the command line
– Familiar with Linux, computational programming, and high-performance computing clusters
– Strong oral and written communication skills
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