Postdoctoral In Bayesian Statistics Jobs in New York

The Department of Materials Design and Innovation at the University at Buffalo invites applications for a full-time Postdoctoral Associate in the Peng Research Group . The successful candidate will conduct research at the intersection of scientific AI, atomistic simulation, computational catalysis, and data-driven materials discovery.

• The position will primarily support a U.S. Department of Energy Genesis Mission project developing closed-loop and agentic AI workflows for chemical-manufacturing research.
• The associate will also contribute to an American Chemical Society Petroleum Research Fund project focused on the data-driven discovery of intermetallic alloy catalysts with unusual electronic structures.
• The research will combine first-principles atomistic simulations, scientific machine learning, reaction modeling, and integration of computational and experimental data.
• The associate will develop reproducible computational workflows, collaborate with researchers across multiple institutions and disciplines, and communicate research findings through publications, presentations, technical reports, software, and research datasets.

• Our benefits , where we prioritize your well-being and success to enhance every aspect of your life.

As an Equal Opportunity / Aff... employer, the Research Foundation will not discriminate in its employment practices due to an applicant's race, color, religion, sex, sexual orientation, gender identity, national origin and veteran or disability status.

• Doctoral degree in materials science and engineering, chemical engineering, chemistry, physics, computational science, or a closely related field. All degree requirements, including the dissertation, must be completed by the date of appointment.
• Demonstrated research experience with density functional theory or closely related first-principles atomistic simulation methods.
• Demonstrated research experience applying artificial intelligence or machine learning to scientific or engineering problems, including the development, training, validation, or evaluation of machine-learning models.
• Proficiency in Python and experience working in Linux and high-performance-computing environments.
• Experience developing or using automated and reproducible computational research workflows.
• Ability to conduct computational research independently and analyze and interpret research data.
• Strong written and oral communication skills and the ability to work effectively in a collaborative research environment.

• Experience with graph neural networks, machine-learning interatomic potentials, or related scientific machine-learning methods for atomistic systems.
• Familiarity with uncertainty quantification, active learning, Bayesian optimization, agentic AI, or closed-loop materials discovery.
• Experience in computational heterogeneous catalysis, electrocatalysis, surface science, electronic-structure analysis, or alloy materials.
• Experience with high-throughput density functional theory calculations, adsorption energies, reaction pathways, transition-state calculations, or microkinetic modeling.
• Experience with scientific software development, version control, research data management, and collaborative code development.

Driving Requirements This position will never drive a university owned vehicle.

Salary Range $60,000

The salary range reflects our good faith and reasonable estimate of the possible compensation at the time of posting, the role and associated responsibilities, and the experience, education, and training of the selected candidate.

37.5 hours per week

North Campus

No

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Contact's Phone 716-645-4621

Posted

Posted 09/02/2026

Number of references required

Number of references required 2

UB is an AA/EOE and welcomes all to apply including veterans and individuals with disabilities. Arrangements will be made if an applicant has a disability in order to provide access to the application, interview and selection process upon request. Reasonable accommodation requests must be made in a timely manner by email at diversity@buffalo.edu or by phone 716-645-2266.