Research Experience for Undergraduates - Intersecting Computing and Evolution

Please note that we are still in the process of finalizing our website.

About our REU Site

Our site will engage and train undergraduate students in empirical research, to advance evolutionary theory, and to harness the principles of evolution for algorithm development and real-world problem-solving. This site aligns with the NSF Big Idea Understanding the Rules of Life and will be supported by mentors experienced in guiding undergraduate students in independent, inter-disciplinary research.

Student projects will focus in two specific domains: (1) digital evolutionary biology and (2) evolutionary computation algorithms. Students will be trained in the scientific process, including literature reviews, developing and executing research questions and experiments, creating software prototypes, and dissemination. Students will also experience professional development activities, participate in seminars, and engage in networking and experiential learning opportunities. Student participants and their mentors will be encouraged to publish their research findings and experiences in peer-reviewed conferences, journals, and competitions, as well as participate in university outreach events.

Program Overview

• Ten week program: May 2026 - July 2026
• Stipend: $7,000 per student
• Travel reimbursement up to $600 per student
• Free housing: Allendale Valley Campus

Application Process

Application window:

• November 30th, 2026 – February 1st, 2027

Eligibility requirements

• Must be a US citizen, national, or permanent resident
• Must be an undergraduate student at an accredited institution in the fall semester following this program
• Must have completed at least 15 college credits before the start of the program
• Student background:
  • Students should be following a program in computing, data science, digital biology, engineering, or mathematics-related disciplines, though consideration will be given to those interested in supporting interdisciplinary research.
• (Nice to have) GPA of at least 3.0 on a scale of 4.0