Back to Listings Tenure-Track: Assistant Professor (CHEN, AI and Machine Learning in Chemical Engineering) Chemical Engineering Location College Station, TX Open Date 8/26/2026 Position ID 190610 Description The Artie McFerrin Department of Chemical Engineering, College of Engineering at Texas A&M University invites applications for a full-time, tenure-track, assistant professor position with a 9-month academic
appointment and the possibility of an additional summer appointment contingent upon need and availability of funds, beginning Fall 2027. The principal focus for this position is at the intersection of computational data science and Chemical Engineering. We are particularly interested in candidates whose research leverages Artificial Intelligence (AI) and Machine Learning (ML) to advance process systems design,
process safety and risk analysis, optimization, characterization, and predictive modeling of materials. The successful candidate is expected to establish and sustain a nationally recognized, externally funded research program that integrates computational data science with chemical engineering. Areas of emphasis may include, but are not limited to, data-driven process modeling and simulation of complex, large-scale
systems; AI-accelerated materials design, including structure-property relationships, self-assembly, and processing optimization; machine learning-driven characterization and stabilization of colloidal systems; physics-informed machine learning; generative models for materials discovery; advanced ML and AI methods for process design, safety and risk analysis, and high-throughput computational screening methodologies
addressing fundamental and applied challenges in chemical engineering. The successful candidate will be expected to conduct original, scholary research; build self-sustaining research programs; teach both graduate and undergraduate courses and mentor students; and contribute an appropriate degree of service to the Department, College, University, and profession. Candidates must demonstrate a strong commitment to
excellence in teaching and mentoring at both undergraduate and graduate levels, as well as active engagement in departmental, college, and professional service. The ideal candidate will articulate a clear vision for integrating experimental, theoretical, and data-driven approaches to solve complex problems at the forefront of chemical engineering research. Qualifications Applicants must hold a Ph.D. in Chemical
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