Tenure-Track Assistant Professor (CHEN, AI and Machine Learning in Chemical Engineering)

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.

Applicants must hold a Ph.D. in Chemical Engineering or a closely related field with an outstanding record of scholarly achievement the ability to secure competitive research funding and evidence of effective teaching and mentorship.