Postdoctoral Associate in Agentic AI, Computational Catalysis, and Machine Learning at Virginia Tech Virginia Tech in United States

Virginia Tech is recruiting multiple Postdoctoral Associates in the research group of Professor Hongliang Xin for work at the intersection of agentic AI, computational catalysis, machine learning, and autonomous scientific discovery.

The positions focus on building AI-native frameworks that combine physics-based modeling, machine-learning methods, knowledge-graph and ontology-based scientific data infrastructures, and agentic workflows for autonomous hypothesis generation, mechanistic exploration, and design of catalytic systems. Research directions include agentic AI for science, computational catalysis and reaction engineering, multiscale modeling, knowledge graphs and scientific data infrastructure, autonomous hypothesis generation and experimental design, and machine learning for catalytic materials discovery.

Eligible applicants should hold a Ph.D. in Chemistry, Chemical Engineering, Materials Science, Physics, Computer Science, or a related field. The PhD must have been awarded no more than four years before the appointment date, with at least one year of eligibility remaining. Strong experience in multiscale/multiphysics modeling relevant to catalysis, machine learning models, reaction kinetics, thermodynamics, and structure-reactivity relationships is expected. Experience with agentic AI, automated data curation, workflow orchestration, ML integration, or AI-assisted experimental design is especially relevant.

This is a full-time appointment available immediately. The initial term is one year, with possible renewal based on performance and funding. Salary starts at $62,232 and is commensurate with experience. Applications are reviewed on a rolling basis until the positions are filled.

To apply, submit a cover letter, CV, contact information for three professional references, and up to three representative publications or preprints through the Virginia Tech application portal.