Reproducibly Parameterizing Molecular Models for High-Throughput Simulation
Faculty Advisor: Dr. Eric Jankowski
The participant will collaborate with teammates to learn and apply scientific software development skills in service of molecular simulation workflows. A key project outcome is stress-testing simulation workflows for choosing and using the interaction parameters for atoms in molecular simulations and making these workflows usable and shareable by others. Prior programming skills are not required, although familiarity with python and bash are pluses. Opportunities to use machine learning techniques, present work at meetings and conferences, and write work for publications will be emphasized.
Role of Participant(s):
The participant will collaborate with teammates to learn and apply scientific software development skills in service of molecular simulation workflows. A key project outcome is stress-testing simulation workflows for choosing and using the interaction parameters for atoms in molecular simulations and making these workflows usable and shareable by others. Prior programming skills are not required, although familiarity with python and bash are pluses. Opportunities to use machine learning techniques, present work at meetings and conferences, and write work for publications will be emphasized.