Ph.D. Student Position – Remote Sensing of Riparian Tree Species
Ecology, Evolution, and Behavior Graduate Program
Boise State University, Idaho, USA
Summary
We are recruiting a Ph.D. student to join a research team developing remote sensing tools to support climate-smart land management in the western United States. The student will work at the intersection of ecology, geospatial data science, and agricultural sustainability, contributing to ongoing USDA-funded research on monitoring and restoring mesic and riparian ecosystems.
The selected student will focus on applying remote sensing and machine learning to develop high-resolution tree species classification models in riparian habitats. This work will support broader project goals of mapping climate adaptation benefits (e.g., water availability), climate mitigation potential (e.g., carbon storage), and biodiversity services in mesic ecosystems. Research will involve integrating multi-sensor satellite imagery (Sentinel-1/2, Landsat, Planet) and lidar, and leveraging deep learning and transfer learning workflows.
Potential research directions include:
- Developing deep learning and transfer-learning models to classify riparian tree species and woody vegetation using fused lidar–optical–radar data.
- Quantifying spatiotemporal patterns of woody vegetation recovery in restored mesic systems.
- Linking tree species distributions to carbon storage, water availability, and biodiversity services in agricultural landscapes.
- Contributing to open, scalable monitoring tools used by land managers, ranchers, and conservation practitioners
The student will be co-advised by Dr. Jodi Brandt and Dr. Trevor Caughlin and will work closely with collaborators in the Ecology, Evolution, and Behavior (EEB) Program and the Human-Environment Systems (HES) group—an interdisciplinary community committed to actionable, stakeholder-driven environmental research.
Qualifications
We seek applicants with training and interest in:
* Remote sensing and geospatial analysis
* Machine learning or deep learning workflows
* Image classification, lidar processing, or multisensor data fusion
* Ecology of riparian or mesic ecosystems (desired but not required)
* Strong quantitative, computational, and programming skills (e.g., Python, R, GEE)
Preferred applicants will have a Master’s degree and prior research experience in remote sensing, spatial data science, ecological modeling, or related fields.
Stipend, Tuition, and Fees
The first two years of the position will be funded by external grants from NASA and USDA, with a minimum salary rate of $33,000/year, a full tuition and fee waiver, and health insurance. We will work with the student to write grant proposals for the final two years of the PhD, and if external funding is not available, Teaching Assistantships will be available to fund the final two years of the PhD. The position begins at any time, and no later than Fall (August) 2026.
To Apply
Submit the following **as a single PDF** (include your last name in the file name):
* Cover letter describing your qualifications, research experience, and career goals
* Curriculum vitae
* Names and contact information for three references
* Unofficial transcripts
Email applications to Dr. Trevor Caughlin [trevorcaughlin [at] boisestate.edu] with the subject line:
“PhD application – EEB program”
Applications are due Monday, January 5th, 2026
Applications will be reviewed as they are received. Top candidates will be invited to apply formally to the Boise State Graduate College. All admissions require approval by the Graduate Dean.
About Boise
Boise is a highly livable city that blends vibrant urban life with exceptional access to outdoor recreation. Nestled in the foothills of the Rocky Mountains, Boise consistently ranks among the best cities to live in the United States, offering year-round opportunities for hiking, skiing, cycling, and river recreation, as well as a thriving arts and culture scene. Learn more at: (https://www.cityofboise.org/).