Postdoctoral Associate, Materials Design and Innovation

University at Buffalo; Town of Amherst (NY); On-site; USD 54,000 - 66,000; Full time

Job summary

The University at Buffalo invites applications for a full-time Postdoctoral Associate in the Peng Research Group to advance research at the intersection of scientific AI, atomistic simulation, computational catalysis, and data-driven materials discovery.

The position supports DOE Genesis Mission projects on closed-loop AI workflows for chemical manufacturing and data-driven discovery of intermetallic catalysts, involving first-principles simulations, machine learning, and collaboration across

Qualifications

• Doctoral degree in materials science and engineering, chemical engineering, chemistry, physics, computational science, or a closely related field; all degree requirements completed by appointment date.
• Experience with density functional theory or related first-principles simulations.
• Experience applying AI/ML to scientific or engineering problems, including model development, training, validation, or evaluation.
• Proficiency in Python and experience in Linux and HPC environments.
• Experience developing automated and reproducible computational research workflows.
• Ability to conduct computational research independently and interpret data; strong written and oral communication.

Responsibilities

• Support research on scientific AI, atomistic simulation, computational catalysis, and data-driven material discovery.
• Develop reproducible computational workflows and workflows for research data management.
• Collaborate across institutions to communicate findings through publications, presentations, and software.
• Contribute to projects on DOE Genesis Mission and data-driven catalyst discovery.

Skills

Python

Linux

HPC environments

Workflow automation

Communication

Education

PhD in materials science and engineering or related field

Job description

Postdoctoral Associate, Materials Design andInnovation

Position Information

Position Title: Postdoctoral Associate, Materials Design andInnovation

Department: Department of Materials Design andInnovation

Posting Link: https://apptrkr.com/9801692 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:

• Our benefits, where we prioritize your well-being and success to enhance every aspect of your life.
• Being a part of the University at Buffalo community.

As an Equal Opportunity / Affidavit Employment 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.

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.

Salary Range

$60,000

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: [e-mail]

Contact's Phone: [phone]

Posting Dates

Posted: 09/02/2026