REU site: interdisciplinary computational biology (ICOMPBIO)

The National Science Foundation Division of Biological Infrastructure awarded the University of Tennessee at Chattanooga $464,970 on May 1, 2026, to operate an REU Site in Interdisciplinary Computational Biology (ICOMPBIO) under the Biological Sciences program (CFDA 47.074).

The site will train 10 students annually for 10 weeks during summers 2026–2028 in computational approaches across genomics, epidemiology, geology, ecology, evolution, biochemistry, cell biology, and molecular biology. Training emphasizes both computing and life sciences competencies alongside soft skills to prepare participants for careers in interdisciplinary STEM. Research projects integrate computational and biological methods to address complex scientific questions, including artificial intelligence applied to metabolite identification, bioinformatic analysis of bacterial proteins, viral infection spread modeling, biodiversity responses to environmental stress, and quantum approaches for biological data analysis. Participating departments span Computer Science and Engineering, Biology, Geology and Environmental Science, Mathematics, Physics, Chemical Engineering, and Engineering Management and Technology. Students begin with Python training and many present results at scientific conferences. The program aligns with NSF priorities in biotechnology, artificial intelligence, and quantum information science. Assessment occurs through Qualtrics; applications are submitted via NSF ETAP.

Place of performance is Chattanooga, Tennessee. The period of performance extends from May 1, 2026, through April 30, 2029.

Abstract

This REU site award to the university of tennessee at chattanooga (UTC), located in chattanooga, TN, will support the training of 10 students for 10 weeks during the summers of 2026-2028. The program, interdisciplinary computational biology (ICOMPBIO), will provide research training in developing computational approaches across genomics, epidemiology, geology, ecology, evolution, biochemistry, cell biology, and molecular biology. The program will enhance participants' knowledge and research skills in both computing and life sciences, as well as soft skills, thereby better preparing them for careers in interdisciplinary stem fields. IT will also strengthen the campus research community, bring in talented students from other institutions, and raise the university?S visibility as a place where innovative, student-centered research happens. Students will learn how research is conducted, and many will present the results of their work at scientific conferences. Assessment of this program will be done through qualtrics. Students should apply to the REU site using NSF etap (education and training application: https://etap.NSF.GOV). The training students will receive is aligned with the NSF priorities in biotechnology, AI, and quantum information science. The ICOMPBIO research projects integrate computational and biological approaches to address complex scientific questions. Example projects include applying artificial intelligence to metabolite identification, using bioinformatic tools to analyze bacterial proteins, modeling the spread of viral infections, studying biodiversity responses to environmental stress, and exploring quantum approaches for biological data analysis. Participating departments include computer science and engineering, biology, geology and environmental science, mathematics, physics, chemical engineering, and engineering management and technology. Students will begin with training in python, data science, and machine learning, then work closely with faculty mentors on research projects while also participating in seminars, workshops, and presentation training. The program includes instruction in ethics and responsible conduct of research, along with mentoring on communication, teamwork, and the social responsibilities of science. Post-program surveys will be conducted. And overall effectiveness by tracking REU-related research outcomes, including publications and conference presentations, as well as longer-term post-graduation pathways such as graduate study and career trajectories. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the foundation's intellectual merit and broader impacts review criteria.- subawards are not planned for this award.