Digital Ecology and Natural Resources Fellowship
Digital Ecology and Natural Resources Fellowship
Tech-powered training for natural resource professionals
The Digital Ecology and Natural Resources Fellowship is for early-career professionals, career changers and students who want to develop expertise and advance their careers.
Participants will gain experience with:
- Drones (UAS) for high-resolution forest monitoring
- Environmental sensors for real-time data collection
- AI and machine learning for resource decision-making
- Hands-on training + mentorship from experts in the Institute for Digital Forestry and our partners from
agencies, industry and other organizations
What's included in the fellowship?
- Year-long coursework, mentoring and coaching
- 3-week immersive residential summer short course (Digital Data Acquisition Camp)
- Monthly virtual professional development sessions
- Team-based projects using real-world datasets
This program, including Digital Data Acquisition Camp, is available at low to no cost, with generous support for participant expenses, covered by the National Science Foundation through an ExLENT program grant.*
apply to the fellowship program
Applications for fellowships are being accepted now! The first cohort launches July 2026.
If you have questions before applying, email DENR@purdue.edu.
Who should apply?
This program is ideal for:
- Early-career professionals
- Professionals in forestry, ecology, wildlife, environmental science or related areas who want
to upskill or retrain - Graduate or upper-level undergraduate students
Applicants should have at least six credits of junior-level or above statistics and/or programming (coding) to be considered.
More Opportunities
Learn about more about the Digital Data Acquisition Camp and other professional development and educational opportunities offered through Purdue's Institute for Digital Forestry and the Department of Forestry and Natural Resources.
Visit our Education and Workforce Development page.
* This work is based upon work funded by the National Science Foundation through the Experiential
Learning for Emerging and Novel Technologies (ExLENT) program, grant #2526215.