GGrantIndex
← Search

REU Site: Sustainability Institute for Machine learning and Collaborative Open-source Development of Enzymatic Simulations (SIMCODES)

$465,000FY2024MPSNSF

Iowa State University, Ames IA

Investigators

Abstract

This Research Experiences for Undergraduates (REU) site award to Iowa State University, located in Ames, IA, supports 10 students for 10 weeks during the summers of 2024-2026. In this program, funded by the Division of Chemistry, students will contribute to multidisciplinary cutting-edge research spanning chemistry, biochemistry, machine learning (ML), and computer science. Participants will gain hands-on research experience in software development, chemical simulation, data analysis, and responsible and ethical conduct of research. Professional development opportunities include weekly research seminars, bootcamps, and informal networking events. Ultimately, this REU site seeks to expose and better prepare more students for participating in STEM-related activities, particularly early career students who may not have had exposure opportunities otherwise. Predicting next generation enzymatic catalysts via simulations is an important, pressing, multidisciplinary problem that requires developments in the fields of computational chemistry, biochemistry, and computer science to develop software, simulation, and analysis techniques. The Sustainability Institute for Machine Learning and Collaborative Open-source Development of Enzymatic Simulations (SIMCODES) will provide individualized research projects for REU participants designed to (1) simulate protein and enzyme processes; (2) use ML methods to replace more expensive simulation methods; (3) use fragment-based quantum mechanics methods to quickly generate additional ML training data; (4) train ML models which can generalize results from one set of enzymes to another; and (5) develop interpretable ML models for predicting catalytic performance of enzymes. 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.

View original record on NSF Award Search →