Description
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 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.
Qualifications
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 Instructions
Applications received prior to January 15, 2027 will receive full consideration. Candidates who apply on or after January 15, 2027 will be considered on a rolling basis until the position is filled. The below documents are required and must be submitted through Interfolio.
1) Cover letter
2) Curriculum Vitae,
3) Research statement (3 pages maximum)
4) List of sponsored research funding, including applicants role on each award
5) Teaching and mentoring statement (3 pages maximum)
6) Teaching evaluations (if available may be uploaded to "other materials"),
7) Names and contact information of three references.
Candidates invited for on-campus interviews will be required to deliver a presentation and provide written references.
All application materials must be submitted online. Please use the Apply Now button to begin your application. For technical support, please visit Interfolio's Support Site (https://support.interfolio.com/) or reach out to their Scholar Service Team at [redacted] or [redacted].
For questions regarding this position, please contact search chair, Dilip Gersappe at Dilip. [redacted].
Special Notes:
This is a tenured faculty position. FLSA Exempt position, not eligible for overtime. In addition to base salary, this position is eligible for $4,150 UUP annual location pay. Internal and external search to occur simultaneously.
Anticipated Start Date: Fall 2027
Department description:The Materials Science and Chemical Engineering department is part of the College of Engineering and Applied Sciences (CEAS), which consists of nine academic departments, as well as the Center of Excellence in Wireless and Information Technology (CEWIT) and the Advanced Energy Research and Technology Center (AERTC). The department has been successful in obtaining more than $10 million in external funding for research and currently has the highest per capita faculty funding within the University that tops the list for research funding in the College of Engineering and Applied Sciences. We also benefit from having a close connection with Brookhaven National Labs, with a number of affiliated faculty, and students that utilize BNL facilities for their research Located 20 miles from Stony Brook, BNL is a multidisciplinary research laboratory supporting world-class scientific programs utilizing state-of-the-art facilities such as the Relativistic Heavy Ion Collider, the National Synchrotron Light Source, and the Center for Functional Nanomaterials, and the NewYorkBlue IBM BG/L P supercomputer. As such, many opportunities exist for collaborative research, and, in some cases, joint appointments can be arranged.
IACS Description: IACS faculty and students are academic and research leaders through the development, dissemination, and facilitation of computation, including AI, high-performance computing, simulation, and data science. IACS-affiliated researchers collaborate on interdisciplinary, high-impact problems with application scales spanning from laptops to supercomputers and the cloud. IACS and DoIT's Research Computing group offer world-class computing resources and staff, including SeaWulf and NVWulf HPC clusters, and the Stony Brook Supercomputer Center (SBSC) that operates Kitsune for the NSF national cyberinfrastructure. IACS also eliminates barriers through support and training for students and faculty, with a strong commitment to diversity.
