University of Minnesota Equivariant Neural Network REU
Program Overview
The University of Minnesota Equivariant Neural Network Research Experience for Undergraduates (REU) is a six-week intensive research program held from May 27 to July 3, 2025. This program offers undergraduate students the chance to explore innovative research in machine learning, with a particular emphasis on:
- Designing equivariant neural networks to handle partial symmetries.
- Utilizing these methods for real life applications.
Participants will collaborate with program faculty and graduate student mentors in a dynamic and supportive environment. Dedicated office space in the School of Mathematics will be provided, ensuring daily access to mentors and essential resources.
Program Benefits
- Stipend: $3,600 for the program duration.
- Travel and Living Support:
- Up to $600 for transportation costs for non-local participants.
- Covered living expenses and meals for non-local participants.
Eligibility
The program is open to undergraduate students who meet the following criteria:
- Pursuing an associate or bachelor’s degree.
- U.S. citizens, permanent residents, or U.S. nationals.
Application Deadline
All application materials must be submitted by February 9, 2024.
Applicant Requirements
We are looking for candidates with the following qualifications:
- Familiarity with basic group theory.
- Ability to read and understand Python code.
- (Preferred) Experience with TensorFlow.
Required Documents
Applicants should prepare and submit the following:
- A Statement of Interest in the program.
- One reference letter (to be submitted online by the reference writer via the application site).
- An unofficial transcript listing all relevant coursework.
Application Link
We look forward to reviewing your application and welcoming you to the University of Minnesota this summer!