Associate or Full Professor – Computational Materials Science
Listed on 2026-01-03
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Education / Teaching
University Professor, Academic
Associate or Full Professor – Computational Materials Science FACULTY VACANCY ANNOUNCEMENT
The City College of New York is pleased to announce a faculty search as part of the CUNY Martin S. Spergel Initiative supported by the Simons Foundation. The CCNY Department of Chemistry and Biochemistry seeks a mid- to senior‑career hire (Associate/Full Professor) in Computational Chemistry/Materials Science, or closely related field.
The successful candidate will join the CUNY AI‑Biome Initiative, a new multi‑campus research effort building on research strengths in bio‑inspired materials, sustainable chemistry, nanotechnology and computational chemistry, with a focus on integrating artificial intelligence and autonomous experimentation to accelerate data‑driven molecular materials discovery and sustainable manufacturing. The appointee will coordinate computational efforts within the AI‑Biome cluster and play a leadership role in shaping this interdisciplinary research community.
Desired areas of expertise may include, but are not limited to:
- Familiarity with universal descriptors for structure/reactivity of surfaces and interfaces.
- Development of accurate, efficient, and transferable many‑body potentials.
- AI‑accelerated modeling of strongly correlated electronic systems.
- Predictive modeling for self‑organizing and bioinspired materials.
- Autonomous and AI‑guided experimental workflows for materials discovery.
The successful candidate will collaborate with experimental groups across CUNY, including the Advanced Science Research Center (ASRC), build partnerships and work with external organizations, including Empire AI. In addition to developing an independent research program, the selected faculty member will play a key role in recruiting and mentoring three new Assistant Professors in complementary areas of materials science, AI‑driven scientific discovery, and sustainable design, helping to shape the long‑term vision of the AI‑Biome initiative.
The position aligns with CCNY’s strengths in sustainable energy materials, catalysis, molecular assemblies, and quantum materials, and leverages CUNY’s collaborative network, including CUNY’s Advanced Science Research Center, the ASRC CAT program that supports industry partnerships, the newly established Empire AI program, and highly active external funding programmes (including PhD training) supported by federal agencies such as NSF, NIH, DoD, and DoE, and major foundations.
Applicants for this position would demonstrate an outstanding record of research accomplishments, strong teaching credentials, and established leadership in their field. The successful candidate will be expected to contribute to the advancement of the department and the College by sustaining a robust, externally funded research programme; engaging actively in undergraduate and graduate teaching and mentoring; and fostering multidisciplinary research and educational collaborations across CCNY and the broader CUNY community.
QUALIFICATIONSFor Associate or Full Professor:
Ph.D. (or foreign equivalent) in computational chemistry/materials science, or closely related field.
Preferred Qualifications- Strong record of research performance in computational materials science.
- Established leadership in the field, with evidence of interdisciplinary activities.
- Demonstrated ability to secure external funding and manage a research group.
- Significant postdoctoral and managerial research experience in the relevant field.
- Experience mentoring student researchers and university‑level teaching.
- Expertise applying AI, machine learning, or quantum methods to materials design.
- Background in modelling complex molecular systems, self‑assembly, or surfaces/interfaces.
- Candidates must be legally authorised to work full‑time in the United States.
Associate Professor: $121,194 - $129,041
Full Professor: $122,201 - $155,388
CUNY offers faculty a competitive compensation and benefits package covering health insurance, pension and retirement benefits, paid parental leave, and savings programmes. We also provide mentoring and support for research, scholarship, and publication as part of our commitment to ongoing faculty…
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