|Job Type||Student / postdoc|
|Salary Details||The current stipend for this opportunity is $55,000 to $65,000 per year depending on experience.|
|Deadline||Dec 22, 2023|
|Required Experience||0 - 1 years|
*Applications will be reviewed on a rolling-basis.
USFS Office/Lab and Location: A postdoctoral research opportunity in large fire simulation modeling is available with the U.S. Department of Agriculture (USDA) U.S. Forest Service (USFS), Pacific Northwest Research Station (PNWRS) located in Corvallis, Oregon.
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 Project: Under mentorship of experts, the participant will learn to calibrate and run the Large Fire Simulator (FSim), analyze its output, and conduct research alongside collaborators to integrate the results into a platform for assessing risk to carbon stocks. FSim is a 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 to pre-process climate and other geospatial data for input into FSim.
- Learn to run FSim.
- Learn to process the large ensemble of spatial data output by FSim.
- Participate alongside collaborators to process and link the FSim output with a framework for calculating wildfire risk to forest carbon stocks.
- 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.
Anticipated Appointment Start Date: December 2023. Start date is flexible and will depend on a variety of factors.
Appointment Length: The appointment will initially be for one year, but could be extended upon recommendation of USFS 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. The current stipend for this opportunity is $55,000 to $65,000 per year depending on experience.
Citizenship Requirements: This opportunity is available to U.S. citizens and Lawful Permanent Residents (LPR).
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 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 ORISE.USFS.PNWRS@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. Degree must have been received within the past six years.
- Experience with ecological or environmental models.
- Experience analyzing large spatial datasets for ecological, environmental or earth science research.
- Knowledge of wildfire science literature.
- Ability to analyze large, complex spatial datasets using a data analysis package, such as R or Matlab.
- Ability to analyze large, complex spatial datasets using geographic information system (GIS).
- Ability to author or co-author peer-reviewed journal articles.
- Ability to make publication-quality figures and maps.
- Ability to work effectively in a highly collaborative team setting.
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