Accelerating Discovery through AI

Qualifications

• The ideal candidate will have a strong background in AI and materials science, with expertise in machine learning, computer vision, large language models, optimization, and deep learning
• Candidates must have completed a Ph.D. degree prior to their start date and possess expertise in information systems, computer science (particularly machine learning and AI), statistics, materials science and engineering, chemistry, mechanical engineering, chemical engineering, electrical engineering, or a related area
• Successful candidates will be expected to create undergraduate and graduate learning environments that address the needs of students from diverse backgrounds, develop an externally sponsored research program, mentor graduate students, collaborate with other faculty, and engage in service to the university and the profession

Full Description

UT Austin seeks applicants for tenure-track faculty positions in AI for materials science. The ideal candidate will have a strong background in AI and materials science, with expertise in machine learning, computer vision, large language models, optimization, and deep learning.

Candidates must have completed a Ph.D. degree prior to their start date and possess expertise in information systems, computer science (particularly machine learning and AI), statistics, materials science and engineering, chemistry, mechanical engineering, chemical engineering, electrical engineering, or a related area.

Successful candidates will be expected to create undergraduate and graduate learning environments that address the needs of students from diverse backgrounds, develop an externally sponsored research program, mentor graduate students, collaborate with other faculty, and engage in service to the university and the profession.