PhD and Postdoctoral Positions in AI-Driven Soft Materials Design at the University of South Carolina University of South Carolina in United States

Dr. Shengli (Bruce) Jiang is launching the Computational Materials and Product Design Group at the University of South Carolina, within the Molinaroli College of Engineering and Computing and the Department of Chemical Engineering. The group’s research centers on soft materials for energy and the circular economy, combining molecular simulation, machine learning (including generative AI and geometric/topological deep learning), and theory to design materials and material-derived products that are high-performing, synthesizable, stable, and scalable.

Openings are available for fully funded PhD students and a postdoctoral researcher. Research areas include plastic upcycling and circular polymers, polymer electrolytes and ion-conducting membranes, and multiscale modeling of soft materials in complex fluids and processing. The postdoctoral role is especially suited to candidates with experience in molecular modeling and simulation, statistical mechanics, mesoscale modeling, generative AI, physics-informed machine learning, polymer science, or complex fluids.

PhD applicants should have a bachelor’s degree in chemical engineering or a related field; a computational background is preferred but not required. Postdoctoral applicants should have a PhD in a relevant field or be near completion. The post does not mention a formal deadline, but it notes that Fall 2026 applicants are encouraged to contact Dr. Jiang as soon as possible.

To apply, send the requested materials as a single PDF to [email protected] with the appropriate subject line for PhD or postdoc applications. The post includes links to the group page, department page, and the announcer’s LinkedIn profile.