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Computational Soft Materials Design and Discovery

 

The Guo Group uses molecular simulations to understand and design functional soft materials, with global sustainability and health challenges in mind. We work at the intersection of molecular simulations, machine learning, and information theory, where we discover and design tunable organization and structure in biomolecular, polymeric, and colloidal materials. We develop the new computational tools necessary to take an information- and data-driven approach toward soft materials engineering, making resourceful use of vast amounts of simulation data.

We are currently seeking motivated graduate and undergraduate students interested in modeling polypeptides and colloids with approaches that utilize machine learning and information theory. Students should have a strong background and interest in the physical sciences and mathematics. Previous experience in computer programming or molecular simulation is helpful but not required.

Graduate students currently in a Ph.D. program at Rutgers are encouraged to contact Prof. Guo by email to discuss potential opportunities in the lab and research interests. Prospective CBE graduate students are encouraged to reach out as well and should apply to the CBE program [https://cbe.rutgers.edu/admissions/graduate-cbe]. Undergraduate students interested in joining the group are welcome to inquire about opportunities in the group by emailing Prof. Guo with a copy of their CV that includes relevant coursework.