*Applications will be reviewed on a rolling-basis.

USDA Forest Service Office/Lab and Location: A fellowship opportunity is available with the US Department of Agriculture (USDA) Forest Service (FS) within the Rocky Mountain Research Station (RMRS) located in Fort Collins, Colorado.

At the heart of the USDA 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 USDA 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 Project: The participant will study risks from wildfire to water supplies in the United States, particularly around priority landscapes in the Wildfire Crisis Strategy (https://www.fs.usda.gov/managing-land/wildfire-crisis/landscapes) The study examines risk to water supplies pre- and post-fuels treatments and estimates the economic return of those treatments. The opportunity sits at the intersection of economic research and policy. As such, the fellow will have the chance to develop a research plan, conduct analysis, and present final results to the US Forest Service Washington Office. 

Learning Objectives: The participant will have the opportunity to learn about federal decision making and the role economic valuation plays in that process. The participant will advance their statistical and modeling skills and learn how to effectively communicate science results to policymakers and land managers. The research is highly collaborative with the chance to work with other economists and across interdisciplinary teams. 

Mentor: The mentor for this opportunity is Travis Warziniack (travis.w.warziniack@usda.gov). If you have questions about the nature of the research, please contact the mentor.

Anticipated Appointment Start Date: 2024/2025.  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 extended upon recommendation of USDA Forest Service and is contingent on the availability of funds.

Level of Participation: The appointment is part-time.

Participant Stipend: The participant will receive a monthly stipend commensurate with educational level and experience that will not exceed $80,500 per year.

Citizenship Requirements: This opportunity is available to U.S. citizens and Lawful Permanent Residents (LPR) only.

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 USDA Forest Service. Participants do not become employees of USDA, USDA Forest Service, 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 ORISE.USFS.RMRS@orau.org and include the reference code for this opportunity.

Qualifications

The qualified candidate should be currently pursuing or have received a bachelor's, master's, or doctoral degree in the one of the relevant fields (e.g. economics, business, hydrology, or related fields). Degree must have been received within the past one year, or anticipated to be received by 5/29/2026.

Preferred skills:

• Some evidence of quantitative skills in either statistics, computational modeling, or GIS is preferred as is evidence of proficiency in English writing and speaking.