Job Title: Student Project/Internship
Organization: 9H SmartRanch Drone Operations
Location: UW campus and nearby Laramie-area ranch, some remote work possible
Position Overview: In this internship/project, a team of four UW students will apply their collective education, training, and experience in addressing research questions related to identification of weed species using drone-mounted sensors, image processing software, and machine learning techniques. Students will further explore the use of drones for precise herbicide application and mosquito breeding abatement. The team will be mentored by faculty from UW’s interdisciplinary Geospatial Information Science & Technology (GIST) Program. Students will utilize state-of-the-art drone equipment and drone image processing software. Above all, participants will be paid to gain hands-on problem-solving experience working collaboratively in a team environment to generate viable solutions that can be implemented in the industry.
This project is ideal for qualified students based in Laramie during the Summer of 2022 who may be looking to combine this opportunity with summer school or other flexible, part-time employment.
- All currently enrolled UW undergraduate or graduate students
o Two of the four students selected must be enrolled in the College of Engineering and Applied Sciences.
- Desired qualifications include some background in one or more of the following areas: (a) drone technology, (b) engineering projects, (c) crop science / weed identification, (d) remotely-sensed image analysis, (e) machine learning techniques.
- Other requirements:
- Participation in WyGISC GeoAI Workshop
- Participation in WyGISC / CEAS Drone Boot Camp
- Participation in Wyoming UAS Symposium
Pay: Each student will receive compensation in two forms:
- Progress Awards: $2,000 – $2,500 upon successful completion of various project milestones
- Hourly Pay: $12/hour – up to $1,500 per student
Application Deadline: March 4, interviews of finalists will be held the week of March 7. Successful applicants will be notified by March 18.
How to Apply: Interested individuals should submit the following:
- Cover letter, expressing why you are interested in this opportunity and your qualification (coursework, training, experience) in one or more of the following areas: (a) drone technology, (b) engineering projects, (c) crop science / weed identification, (d) remotely-sensed image analysis, (e) machine learning techniques.
- Current resume, including GPA
- Submit to: firstname.lastname@example.org