What are the responsibilities and job description for the USGS UAS and Satellite Remote Sensing to Survey Vegetation Conditions position at Zintellect?
*Applications will be reviewed on a rolling-basis.
USGS Office/Lab and Location: A research opportunity is currently available with the U.S. Geological Survey (USGS) located in Boise, Idaho
The USGS mission is to monitor, analyze, and predict current and evolving dynamics of complex human and natural Earth-system interactions and to deliver actionable intelligence at scales and timeframes relevant to decision makers. As the Nation's largest water, earth, and biological science and civilian mapping agency, USGS collects, monitors, analyzes, and provides science about natural resource conditions, issues, and problems.
Research Project: This mentored opportunity focuses on developing AI/ML and time-series remote sensing approaches to characterize fine-scale vegetation composition and configuration in the intermountain west. The project includes advancement of UAS (drone) survey techniques to assess vegetation conditions and potential fire behavior effects. You will train in classifying satellite and UAS imagery using AI/ML methods and gain experience in the development of geospatial models linking field and remotely sensed data. Activities will be tailored to your background and interests, with emphasis on coding, GIS modeling, and imagery analysis.
Activities for this internship would be dependent on candidate experience, interests, and capabilities. The primary Activities of this internship would be the classification of remotely sensed imagery from satellites and UAS with AI/ML techniques to characterize composition and configuration of vegetation. This data would be used by the intern to help in the training of geospatial models relating field data to satellite or UAS-derived imagery. Coding, GIS modeling, and imagery analysis tasks could be split flexibility to meet a student’s interest and ability.
Learning Objectives: You will gain experience in remote sensing, GIS, UAS applications, and AI/ML-based image analysis within an applied research and development setting. The internship will build skills in reproducible data processing and analysis using coding tools such as Python and notebook-based workflows. Through mentorship and project collaboration, you will strengthen technical, analytical, and scientific communication skills relevant to landscape ecology and fire science.
Mentor: The mentor for this opportunity is Jason Kreitler (jkreitler@usgs.gov). If you have questions about the nature of the research please contact the mentor(s).
Anticipated Appointment Start Date: June 15, 2026. Start date is flexible and will depend on a variety of factors.
Appointment Length: The appointment will initially be for 10 weeks, but may be renewed upon recommendation of DOI and is contingent on the availability of funds.
Level of Participation: The appointment is full time.
Participant Stipend: Stipend rates may vary based on numerous factors, including opportunity, location, education, and experience. If you are interviewed, you can inquire about the exact stipend rate at that time and if selected, your appointment offer will include the monthly stipend rate.
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 USGS. Participants do not become employees of USGS, 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: If you have questions about the application process please email USGS@orau.org and include the reference code for this opportunity.