Job Type: Student / postdoc
Salary Details: The current stipend for this opportunity is $5,500 to $6,500 per month.
Deadline: Aug 18, 2023

USFS Office/Lab and Location: A postdoctoral research fellowship is available at the US Department of Agriculture (USDA) Forest Service (USFS), Pacific Southwest Research Station to collaborate with partners at the University of Texas at Austin and Simon Fraser University. The appointment is in Davis, California, and there is an opportunity to participate remotely. The fellowship will begin in Summer 2023 with a flexible weekly schedule and will continue through September 2024 with the potential for an extension contingent on funding. 

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: We are seeking a qualified candidate to collaborate with the USDA Forest Service and partners to investigate subsurface drivers of watershed response to drought. We seek a fellow with interests in coupling observational insights from intensively monitored study catchments with remote sensing, hydrological modeling, and/or machine learning methods to upscale process understanding to large watersheds. Diverse backgrounds will be considered, but candidates with Python programming, remote sensing, hydrological modeling, and/or machine learning experience will be given preference. For additional topical context, interested candidates can review recently published manuscripts from this funded project:

Learning Objectives: As a result of this appointment, the participant will improve their skills in physical and theoretical hydrology, field data collection, analysis of remote sensing data, and data processing and analysis for Earth systems data. 

MentorThe mentor for this opportunity is David Dralle ( If you have questions about the nature of the research, please contact the mentor.

Anticipated Appointment Start Date: August 1, 2023.  Start date is flexible and will depend on a variety of factors.

Appointment Length: The appointment will initially be for fourteen months but may 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 $5,500 to $6,500 per month. 

Citizenship Requirements: This 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 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 and include the reference code for this opportunity.


The qualified candidate should have received a doctoral degree in one of the relevant fields or be currently pursuing the degree with completion before the appointment start date.

Preferred Skills:

  • Demonstrated technical writing and communication skills
  • Python coding
  • GIS


Apply at this link: