AI for Materials Discovery — Tenure-Track Professorship

City University of New York; New York (NY); Presencial; USD 90 000 - 113 000; Tempo integral

Resumo da oferta

Hunter College, part of the City University of New York, seeks a tenure-track Assistant or Associate Professor in AI for Materials Science. The position emphasizes research at the AI-materials interface, collaboration with experimentalists, and education across undergraduate and graduate programs.

The successful candidate will build an externally funded program, contribute to teaching, and develop innovative courses at the AI-materials nexus, within CUNY's strong ecosystem including ASRC and AI

Qualificações

• Ph.D. (or foreign equivalent) in computer science, or closely related field.
• Strong research record in AI for scientific discovery, particularly in materials science, chemistry, or closely related fields.
• Experience developing AI methods to accelerate scientific discovery, such as generative modeling or structure–property modeling.
• Experience developing AI-guided scientific workflows and autonomous experimentation.
• Demonstrated ability to lead interdisciplinary research and secure external funding.

Responsabilidades

• Establish and sustain a robust, externally funded research program.
• Contribute to undergraduate and graduate teaching and mentoring.
• Develop new educational programming at the intersection of AI and materials science.
• Collaborate with experimental researchers to translate computational advances into practical laboratory applications.
• Foster multidisciplinary research and educational partnerships across Hunter College and CUNY.

Conhecimentos

AI for discovery

Autonomous experimentation

Experimental collaboration

Interdisciplinary leadership

Formação académica

PhD in CS or related field

Descrição da oferta de emprego

Hunter College, part of the City University of New York, seeks a tenure-track Assistant or Associate Professor in AI for Materials Science. The position emphasizes research at the AI-materials interface, collaboration with experimentalists, and education across undergraduate and graduate programs.

The successful candidate will build an externally funded program, contribute to teaching, and develop innovative courses at the AI-materials nexus, within CUNY's strong ecosystem including ASRC and AI