USFS Data Science Fellowship to Understand the Influence of Wildfires on Recreation on Public Lands
Organization
U.S. Department of Agriculture (USDA)
Reference Code
USDA-USFS-2023-0173
How to Apply

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A complete application package consists of:

  • An application
  • Transcript(s) – For this opportunity, an unofficial transcript or copy of the student academic records printed by the applicant or by academic advisors from internal institution systems may be submitted.  Selected candidate must provide proof of completion of the degree before the appointment can start.  Click Here for detailed information about acceptable transcripts.
  • A current resume/CV
  • Two educational or professional recommendations. At least one recommendation must be submitted in order for the mentor to view your application.

All documents must be in English or include an official English translation.

Application Deadline
7/7/2023 1:23:57 PM Eastern Time Zone
Description

*Applications will be reviewed on a rolling-basis.

USFS Office/Lab and Location: A fellowship opportunity is available with the US Department of Agriculture (USDA) Forest Service (USFS) within the Pacific Northwest Research Station located in Seattle, Washington.

At the heart of the U.S. Forest Service's mission is their purpose. Everything they do is intended to help sustain forests and grasslands for present and future generations. Why? Because their stewardship work supports nature in sustaining life. This is the purpose that drives the agency’s mission and motivates their work across the agency. It’s been there from the agency’s very beginning, and it still drives them. To advance the mission and serve their purpose, the U.S. Forest Service balances the short and long-term needs of people and nature by: working in collaboration with communities and our partners; providing access to resources and experiences that promote economic, ecological, and social vitality; connecting people to the land and one another; and delivering world-class science, technology and land management.

Research ProjectThe participant will collaborate with researchers on the U.S. Forest Service Pacific Northwest Research Station Landscape Uses and Values Team and University of Washington Outdoor R&D. The goal of our joint research is to use remote and recreation user-generated data to better measure and understand outdoor recreation. The participant will be involved in a project to quantify and characterize recreation use over large landscape areas in the U.S. West that have been prioritized for wildfire risk reduction. Our data and findings will demonstrate how novel approaches to measuring and mapping recreation use can provide information on human values for prioritizing future wildfire management efforts. The participant will support this project by developing software and scripted workflows for ingesting, storing, processing, analyzing, and visualizing spatial data. The methods involve using and improving existing Python and R code, as well as developing new strategies to process data for use in the project. 

Learning ObjectivesThe participant will not only build data science and research skills, but also gain experience participating with actionable research that addresses a natural resource management need and relates to the human dimensions of natural resource management.

MentorThe mentor for this opportunity is Eric White (eric.m.white@usda.gov). If you have questions about the nature of the research, please contact the mentor.

Anticipated Appointment Start Date: 2023.  Start date is flexible and will depend on a variety of factors.

Appointment LengthThe appointment will initially be for three months but may be extended upon recommendation of USFS and is contingent on the availability of funds.

Level of ParticipationThe appointment is part-time (15 hours per week).

Participant StipendThe participant will receive a monthly stipend commensurate with educational level and experience. The current stipend rate for this opportunity is $35/hour.

Citizenship RequirementsThis 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 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 USFS. Participants do not become employees of USDA, USFS, 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 USForestService@orise.orau.gov and include the reference code for this opportunity.

Qualifications

The qualified candidate should be currently pursuing or have received a master's or doctoral degree in one of the relevant fields. Degree must have been received within 5 years of the appointment start date.

Preferred Skills:

  • At least 2 years of experience programming R and/or Python in an academic or professional setting.
  • Demonstrated success working with large and varied sources of data, including geospatial data.
  • Ability to troubleshoot, problem-solve, and work independently.
  • Excellent organizational, teamwork, and communication skills.
  • Demonstrated experience with a version control system, such as git.
  • Interest in outdoor recreation, forestry, and/or fire management.
Eligibility Requirements
  • Degree: Master's Degree or Doctoral Degree received within the last 60 months or currently pursuing.
  • Academic Level(s): Graduate Students, Postdoctoral, or Post-Master's.
  • Discipline(s):
    • Computer, Information, and Data Sciences (17 )
    • Earth and Geosciences (21 )
    • Engineering (27 )
    • Environmental and Marine Sciences (14 )
    • Life Health and Medical Sciences (48 )
    • Mathematics and Statistics (11 )
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