USDA-FS Fellowship in Large Fire Simulation Modeling

*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 Pacific Northwest Research Station (PNWRS) located in Corvallis, Oregon.

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: Under mentorship of experts, the participant will learn about the Large Fire Simulator (FSim), analyze its output alongside various ancillary environmental and demographic spatial datasets, and conduct research alongside collaborators to integrate the results into a climate change impacts analysis paper for publication in a scientific journal. FSim is a mechanistic and stochastic, monte-carlo style model that simulates wildfire ignition, spread and behavior on a gridded landscape. FSim is driven with present-day and future climate data and outputs a large ensemble of gridded spatial data layers. The participant will have an opportunity to participate with a team of scientists conducting research with FSim, and have opportunities to write reports and papers for peer-reviewed journals.

Learning Objectives: Specific learning activities include:

• Learn about the pre-processed climate and other geospatial data for input into FSim.
• Learn how FSim simulations are run.
• Learn to process the large ensemble of spatial data output by FSim.
• Participate alongside collaborators to analyze FSim output for projecting future wildfire impacts to various ecosystem services.
• Survey, read and discuss relevant scientific literature.
• Make maps and figures suitable for publishing in a peer-reviewed journal article.
• Contribute to writing Forest Service general technical report (GTR) chapters and/or peer-reviewed journal articles.

Mentor: The mentor for this opportunity is John Kim (john.kim@usda.gov). If you have questions about the nature of the research, please contact the mentor.

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

Appointment Length: The appointment will initially be for three months but may be extended upon recommendation of USDA Forest Service 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 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.PNWRS@orau.org and include the reference code for this opportunity.

Qualifications

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

Preferred skills:

• Strong foundation in biology, ecology, and/or marine biology
• Experience with R coding language
• Experience with geospatial data analysis
• Experience with ecological models
• Experience authoring or co-authoring peer-reviewed scientific journal articles
• Experience managing large and complex datasets

Eligibility Requirements

• Citizenship: U.S. Citizen Only
• Degree: Master's Degree received within the last 240 month(s).
• Academic Level(s): Graduate Students, Post-Bachelor's, or Post-Master's.