This opportunity is curated through the UF TESI Environmental Leaders Network. Opportunities posted through the Network may not be affiliated with the Florida Museum or TESI, but are shared with UF undergraduate students who want to learn more about environmental research, education and outreach, and civic engagement.
Host Organization
UF Weecology Lab
Type of Position
- Full time
- Fully remote work is possible for this position
- Anticipated salary is $60,000 – $70,000 annually including full benefits
Description
The Weecology lab at the University of Florida has an opening for a computer vision developer to join our team. We use airborne imagery across research programs to monitor trees and wildlife and develop open source tools for the biological monitoring community. The position will contribute to research projects, Python package development, and community outreach. Areas of computer vision research include fine-grained classification, active learning and sensor fusion from data collected from UAVs, crewed aircraft, and (potentially) satellites. Our open source projects include DeepForest, the MillionTrees benchmark, as well as upcoming efforts for a wide array of challenging biodiversity applications.
Ideal candidates will work effectively with a history of responsibility and attention to detail. Independence and a willingness to take ownership over projects is key. Some experience with Python, open-source software development practices, and deep learning frameworks is preferred, but there is also ample room for skill building and mentorship within the lab composed of research scientists, software engineers and biologists. Our lab has a proven track record in developing machine learning software and datasets for ecology. Your work will be valued and used by scientists around the world contributing to biodiversity monitoring with a global reach.
Deadline to Apply
Saturday, November 30th
Apply
Interested applicants should contact Dr. Glenda Yenni (gmyenni@ufl.edu)
In your email, please include as a single attached file: 1) why you are interested in this position (300 words or less) and 2) a resume or CV including descriptions and links to prior work and/or research experience and the responsibilities, skills, and duties involved in those positions.