Empire Innovation Professor (Associate / Full Professor) - AI Informed Materials Science - Department of Material Science & Chemical Engineering (MSCE) & Institute for Advanced Computational Science (IACS) - College of Engineering and Applied Sciences

Role details

The Department of Materials Science and Chemical Engineering and the Institute for Advanced Computational Science (IACS), invites applications to apply for tenure-track Empire Innovation Professor (Associate/ Full Professor) position at Stony Brook University with an expected starting date of Fall 2027. We are seeking an innovative and highly-collaborative researcher focused on the development and applications of artificial intelligence and machine learning to advance the discovery and design of novel materials.

The successful candidate will hold a joint appointment between the department and IACS while engaging with Empire AI, which is a state-of-the-art AI computing center in New York State with an aim of facilitating statewide innovation, research, and development of AI technologies. Applicants with a strong record of excellence and commitment to undergraduate and graduate teaching, including the ability to teach new courses for the development of the Materials Engineering Undergraduate Program, and a proven record of securing competitive external research funding.

The Institute for Advanced Computational Science (IACS) sits at the forefront of data and computing, driving high-impact innovation across the physical, life, environmental, and social sciences, engineering, and the humanities. As an intellectually vibrant ecosystem, IACS unites a diverse, world-class community of core and affiliate faculty, postdocs, research scientists and students dedicated to advancing the fundamental foundations of supercomputing, data science, and artificial intelligence.

By bridging traditional discipline boundaries and fostering interdisciplinary collaboration, the Institute empowers researchers to harness next-generation computational tools to solve humanity’s most pressing challenges. In the Department of Materials Science and Chemical Engineering, our programs in Materials Science and Engineering and Chemical and Molecular Engineering offer students an extensive curriculum with the opportunity to pursue advanced studies and gain knowledge of materials and chemical engineering theory and its relationship to related engineering processes.

Our department is home to many research centers including an EFRC on Energy Storage technologies, the Center for Mesoscale Transport Properties, the Garcia Polymer Center, and the Center for Thermal Spray Technologies. These centers offer a unique and rich environment for interdisciplinary research and education. The current position is expected to strengthen and complement teaching and research activities in materials science and engineering.

The successful candidate is one who demonstrates a motivating philosophy to provide students with a broad knowledge in theoretical and experimental techniques and builds a vibrant research program balancing independent and collaborative research projects while pursuing excellence in teaching at the undergraduate and graduate levels in the Materials Science and Engineering Program. The faculty member will contribute to an inclusive academic community and to collaborative education across the College of Engineering and Applied Sciences and the College of Arts and Sciences.

Candidates must meet the criteria for appointment at the rank of Associate or Full Professor at Stony Brook University and may be eligible for designation as a SUNY Empire Innovation Professor, subject to SUNY approval.

Required Qualifications

Ph.D. in Materials Science or a closely related discipline. A strong record of high-impact, peer-reviewed scholarly publications demonstrating significant research contributions and impact with a history of multidisciplinary collaboration. A proven record of securing competitive external research funding. Internationally recognized research accomplishments in materials science and engineering, including innovation and leadership in the application of artificial intelligence and machine learning to materials discovery and design. A strong record of excellence and commitment to undergraduate and graduate teaching, mentoring, and the development of an inclusive academic environment.

Experience and scholarly accomplishments commensurate with appointment and tenure at Associate or Full Professor rank.

Preferred Qualifications

Demonstrated accomplishments in one or more of the following areas: physics-informed machine learning or AI-enabled multiscale modeling of materials; development and deployment of scalable AI/ML methods on high-performance computing platforms; leadership of multidisciplinary research projects integrating AI/ML with experimental materials synthesis, characterization, data analysis or processing; and development of undergraduate or graduate courses or curricula connecting materials science with artificial intelligence.

Application deadline: 2027-01-14