Collaborative Research: CyberTraining: Implementation: Medium: Establishing Sustainable Ecosystem for Computational Molecular Science Training and Education

Computational research in molecular sciences increasingly involves electronic structure theory, advanced sampling algorithms in molecular dynamics/Monte Carlo, and data science and machine learning using increasingly high-end and complex software and hardware resources. The lack of well-curated training materials and hands-on training opportunities significantly inhibits the progress of the next generation of computational molecular science cyberinfrastructure (CI) users.

This project will establish an institute focused on serving the advanced cybertraining needs of the communities engaged in computational molecular science and engineering (CMSE). To do so, this project will bring together molecular sciences and engineering experts to address this cybertraining challenge through a core committee, invited instructors, advisory board, and community participants.

This project will establish an Institute for Computational Molecular Science Education, which will be designed to create a sustainable ecosystem for training the next generation of research workforce in molecular simulation CI. This project will include educational modules for training in advanced computational tools while bolstering fundamental understanding of underlying theoretical concepts.

The project will encompass summer/winter schools for hands-on training on advanced computational techniques and enhancing peer networking for early-stage researchers, web-based content to support training at a larger scale, and curriculum and instructional materials for undergraduate and graduate courses to support course development in CMSE. This project will train the next generation of professionals in chemical engineering, molecular and materials science, chemistry, and biophysics by providing critical tools in computational and data science.

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.