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USDA-ARS Postdoctoral Fellowship in Insect Diagnostics Investigating Mating Status of Detected Fruit Flies: Hawaii

Job Description

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U.S. Department of Agriculture (USDA)
Hilo, Hawaii
Job Category
Post Doctoral Appointments
Last Date to Apply
*Applications may be reviewed on a rolling-basis. ARS Office/Lab and Location: A postdoctoral research opportunity is currently available with the U.S. Department of Agriculture (USDA), Agricultural Research Service(ARS), located in Hilo, Hawaii. 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: The postdoctoral fellow will contribute research to projects related to the study of tropical insect species that have negative impacts to agriculture in the United States. Potential projects range from population genetics and species/strain diagnostics. Throughout the fellowship, the postdoctoral fellow will gain training and experience in insect genomics, third-generation sequencing and assembly, functional genomics, computational biology, and developing data analysis pipelines. The postdoctoral fellow will also be offered opportunities for intellectual and professional development through access to training webinars and courses through SciNet, an initiative set forth by the USDA Agricultural Research Service (ARS) to improve the USDA’s research capacity by providing scientists with access to high performance computer clusters, cloud computing, improved networking for data transfer and training in scientific computing. Learning Objectives: This postdoctoral opportunity is intended to provide training and research experience in arthropod computational biology, and the research to be performed by this appointment is to support new projects related to the analysis of large data sets that are beyond the scope and capacity of current research projects. Mentor: The mentor for this opportunity is Sheina Sim (sheina.sim@usda.gov). If you have questions about the nature of the research please contact the mentor. Anticipated Appointment Start Date: 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.
The qualified candidate should have received a doctoral degree in one of the relevant fields. Candidates with expertise in computational biology, spatial data analysis, bioinformatics, genomics, or population genetics are encouraged to apply. Preferred Skills: - Previous experience in the analysis of large and complex data sets related to genomics, population genetics, and diagnostics - Fluency in an object-oriented programming language such as python or R - A background in computational biology, bioinformatics, or genomics
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