Assistant Professor -AI for Materials -Fall 2025

Cockrell School of Engineering and College of Natural Sciences at The University of Texas at Austin seek applicants for four tenure-track faculty positions at the rank of Assistant Professor as part of its "AI for Materials" cluster initiative led by the Texas Materials Institute (TMI) and its materials science and engineering graduate program, with appointments to start in the 2025-26 academic year. The faculty positions will be based in a home department and it is broadly expected that the positions will be in the Walker Department of Mechanical Engineering, the McKetta Department of Chemical Engineering, and the Department of Chemistry. However, other home departments might also be appropriate. Collaborative research opportunities will include the Energy Institute, Oden Institute, Texas Advanced Computing Center, Texas Institute of Electronics, the Microelectronics Research Center, Texas Quantum Institute, and with others who will arrive as part of the broader AI initiatives. Open rank positions will be considered for exceptional candidates for the Department of Chemistry.

The vision of the cluster initiative is to strengthen expertise in Foundational AI to accelerate materials research at UT Austin across the general areas of 1. Machine learning for accelerating computational modelling of materials, 2. Computer vision for advanced imaging in materials characterization, 3. Large language models for materials science, 4. Optimization in materials synthesis systems and autonomous high throughput discovery, 5. Deep learning in materials big data. Both experimental and computational research activities will be considered across a board range of existing and emerging topics in materials science. The research activity will also contribute to new educational material, including new courses, that will span across the materials science and engineering program and the home department, as well as teaching new undergraduate data analytics/AI courses at UT Austin.

We are committed to strengthening our leadership in research, development and implementation of artificial intelligence (AI) capabilities to accelerate Materials research, utilizing strengths in the core facilities of the Texas Materials Institute (TMI) and the Texas Advanced Computing Center (TACC). Candidates will be active members of the materials science and engineering graduate program in TMI and their home department.

Candidates must have completed a Ph.D. degree prior to their start date. Candidates in one or more of the following areas will be preferred: information systems, computer science (in particular, machine learning and AI), statistics, materials science and engineering, chemistry, mechanical engineering, chemical engineering, electrical engineering, or a similar related area. Successful candidates will be expected to create undergraduate and graduate learning environments that address the needs of students from a variety of backgrounds, with differing learning approaches and abilities, develop an externally sponsored research program, mentor graduate students, collaborate with other faculty, and be involved in service to the university and the profession. Preferred candidates will have specific interest in cross-disciplinary research in accelerating materials science and engineering using AI. Candidates are encouraged to specify a home department preference when responding to the link below, and to check the relevant department specific faculty postings.

Interested applicants should submit the following materials via -Interfolio link- : (1) a cover letter, (2) curriculum vitae, (3) research statement, (4) teaching and mentoring statement, and (5) a list of three references. Successful candidates will be required to complete an Employment Eligibility Verification form, a background check, and provide documents to verify identity and eligibility to work in the U.S.A.

For full consideration, candidates should submit their applications by 30^th of November.

The University of Texas at Austin, as an equal opportunity/affirmative action employer, complies with all applicable federal and state laws regarding nondiscrimination and affirmative action. The University is committed to a policy of equal opportunity for all persons and does not discriminate on the basis of race, color, national origin, age, marital status, sex, sexual orientation, gender identity, gender expression, disability, religion, or veteran status in employment, educational programs and activities, and admissions.