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USDA-ARS Research Opportunity in Geospatial Analysis

*Applications may be reviewed on a rolling-basis and this posting could close before the deadline.

ARS Office/Lab and LocationA research opportunity is currently available with the U.S. Department of Agriculture (USDA), Agricultural Research Service (ARS), Beltsville Agricultural Research Center, Hydrology & Remote Sensing Laboratory 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: The aim of this project is to support research activities associated with ongoing projects assessing impacts of agricultural conservation practices on ecosystem services.

Under the guidance of a mentor, the participant will be involved in multiple research activities for this project, including:

  • Analyses of entomological, biophysical, habitat, and land use data using statistical or other quantitative methods including applications of standard software used in geospatial analyses and ecosystem modeling
  • Performance of field work activities which support research projects, including installation of field equipment and collection of environmental samples.
  • Performance of laboratory research which will involve preparation of samples,use of analytical equipment, and analyses of analytical results
  • Interpretation and communication of analytical results and generation of summary data products and reports of findings

Learning Objectives: Learning objectives for this opportunity include:

  • Gaining a better understanding of agricultural landscapes and ecosystem services associated with agricultural production.
  • Learning how to conduct geospatial analyses of agricultural landscapes and quantitatively assess conservation practice success.
  • Learning how to sample agroecosystems in conservation practice assessments and how to process associated environmental samples in the laboratory.

Mentor(s)The mentor for this opportunity is Greg McCarty ( If you have questions about the nature of the research support activities please contact the mentor(s).

Anticipated Appointment Start Date: Early 2024.  Start date is flexible and will depend on a variety of factors.

Appointment LengthThe 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 ParticipationThe appointment is full-time.

Participant StipendThe participant will receive a monthly stipend commensurate with educational level and experience.

Citizenship RequirementsThis opportunity is available to U.S. citizens only.

ORISE InformationThis 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 and include the reference code for this opportunity.



The qualified candidate must have received a bachelor's or master's degree in one of the relevant fields.

Preferred skills:

  • Background in geospatial and statistical analyses of environmental data
  • Experience with collection of field data and routine laboratory practices
  • Proficiency with GIS and statistical software such as ArcGIS, R etc.
  • Excellent verbal and written communication skills