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

Texas A&M University • College Station, TX

46d • Onsite

About The Position

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. 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, scholarly 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.

Requirements

• Ph.D. in Chemical Engineering or a closely related field.
• Outstanding record of scholarly achievement.
• Ability to secure competitive research funding.
• Evidence of effective teaching and mentorship.

Nice To Haves

• 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.
• 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.

Responsibilities

• Establish and sustain a nationally recognized, externally funded research program that integrates computational data science with chemical engineering.
• Conduct original, scholarly research.
• Build self-sustaining research programs.
• Teach both graduate and undergraduate courses.
• Mentor students.
• Contribute an appropriate degree of service to the Department, College, University, and profession.
• Demonstrate a strong commitment to excellence in teaching and mentoring at both undergraduate and graduate levels.
• Engage actively in departmental, college, and professional service.
• Articulate a clear vision for integrating experimental, theoretical, and data-driven approaches to solve complex problems at the forefront of chemical engineering research.

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level
• Education Level: Ph.D. or professional degree