Research Opportunity Number: CBE-06

Project Title:  Molecular Modeling and Machine Learning of Polymers

Project Summary: Depending on their underlying chemistry and architecture, polymers, which are large macromolecules comprised of smaller chemical units, are used in a wide variety of applications. Certain polymers are known to be “stimuli-responsive” in the sense that they can drastically alter their characteristics based on environmental conditions. Consequently, they can be used to create “smart,” adaptive materials that alter function in response to triggers like temperature, pH, and stress. In the Webb group, we are interested in developing predictive tools to facilitate the understanding and design of stimuli-responsive polymers. Two forms of predictive tools, enabled by modern computational power, are molecular modeling and machine learning.

Students hosted by the Webb group can expect to work on research problems that help us to improve upon the accuracy of either current molecular modeling approaches or machine learning algorithms that are of interest for predict polymer properties.
Students can expect to perform computational and mathematical work with significant reliance on numerical programming. They will gain exposure to state-of-the-art methods in computational research. In advancement of science, the knowledge and methods generated via these activities will set the stage for future campaigns in polymer design across diverse applications, such as smart sensing, diagnostics, drug-delivery, coatings, clothing, and purification. 

Student Roles and Responsibilities: The student will undertake assignments independently, engage in weekly discussions and deliver timely reports

Additional Considerations:  Start and end dates are flexible, but the student should be available essentially full-time (at least 30 hours/week).

Department/Institute:  Chemical and Biological Engineering

Faculty Sponsor:   Michael Webb

Participation Dates: June 1 -August 15, 2023

Stipend Offered:  $100-400 weekly TBD

Number of Internships Available: 0-3

Application Deadline: March 15, 2023, midnight eastern daylight time