Professor of Computational Materials Science & AI Discovery

City University of New York; New York, Northern (NY, KY); Hybrid; USD 121,000 - 155,000; Full time

Job summary

City College of New York is conducting a faculty search for Associate or Full Professor in Computational Chemistry/Materials Science, aiming to build leadership within the AI-Biome Initiative. The appointee will coordinate computational efforts and help shape an interdisciplinary research community across CCNY and CUNY, mentoring new faculty and advancing sustainable design and data-driven discovery.

The successful candidate will demonstrate an outstanding research record, strong teaching

Qualifications

• Ph.D. (or foreign equivalent) in computational chemistry/materials science, or closely related field.
• Strong record of research in computational materials science.
• Evidence of interdisciplinary leadership and external funding ability.
• Experience mentoring student researchers and teaching at university level.
• Experience applying AI/ML/quantum methods to materials design.

Responsibilities

• Coordinate computational efforts within the AI-Biome cluster.
• Lead interdisciplinary research community across CCNY and the CUNY network.
• Recruit and mentor three new Assistant Professors.
• Develop and lead an independent research program with external funding.
• Engage in undergraduate and graduate teaching and mentorship.

Skills

Computational chemistry

Materials science

AI/ML in materials

Leadership

Funding acquisition

Teaching & mentoring

Interdisciplinary collaboration

Education

Ph.D. in computational chemistry/materials science

Job description

City College of New York is conducting a faculty search for Associate or Full Professor in Computational Chemistry/Materials Science, aiming to build leadership within the AI-Biome Initiative. The appointee will coordinate computational efforts and help shape an interdisciplinary research community across CCNY and CUNY, mentoring new faculty and advancing sustainable design and data-driven discovery.

The successful candidate will demonstrate an outstanding research record, strong teaching