Job Details

University at Buffalo
  • Position Number: 9801690
  • Location: Buffalo, United States
  • Position Type: Laboratory and Research


Postdoctoral Associate, Materials Design and Innovation

Position Information

Position Title: Postdoctoral Associate, Materials Design and Innovation
Department: Department of Materials Design and Innovation
Posting Link: <a href=""https://apptrkr.com/9801690"">https://www.ubjobs.buffalo.edu/postings/64174
Job Type: Full-Time

Posting Detail Information

Position Summary
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.

Learn more:

The Research Foundation of SUNY is an EOE and welcomes all to apply including veterans and individuals with a disability.


Minimum Qualifications
  • 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.


Preferred Qualifications
  • 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.


Physical Demands


Salary Range
$60,000

Special Instructions Summary


Is a background check required for this posting?
No

Contact Information

Contact's Name: Melissa King
Contact's Pronouns:
Contact's Title: Financial Transaction Specialist
Contact's Email: mking23@buffalo.edu
Contact's Phone: 716-645-4621

Posting Dates

Posted: 09/02/2026
Deadline for Applicants:
Date to be filled:







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