Postdoc in Theoretical and Computational Chemistry, ML Methods for Polymers Texas A&M University in United States

Texas A&M University is advertising a postdoctoral research associate position in theoretical and computational chemistry. The group is especially interested in candidates working at the intersection of machine learning, polymer science, and high-throughput experiments, with the main focus on a Scialog project developing ML methods for polymers. There are also opportunities for broader methods development and applications in other ML-related areas of the group.

The position is announced by Daniel Tabor, Assistant Professor at Texas A&M University. The post is clearly a postdoc opening, not a PhD or master's call.

Application deadline: July 29 (preferred start: early September). Applicants are directed to the group openings page for full details and application instructions, and to the Texas A&M application portal for submission.

Research areas/keywords: theoretical chemistry, computational chemistry, machine learning, polymers, high-throughput experimentation, methods development.

Eligibility highlights: no detailed degree, GPA, or language requirements are stated in the post. Interested applicants should review the openings page for complete instructions and reach out to the announcer with questions.