Postdoctoral Research Associate in AI-Accelerated Molecular and Materials Modeling

What You Will Do

The Physics and Chemistry of Materials group (T-1) at Los Alamos National Laboratory seeks a highly motivated Postdoctoral Researcher to develop and apply advanced electronic structure, atomistic simulation, and AI/ML methodologies for understanding and controlling rare‑earth element (REE) chemistry. The successful candidate will work at the intersection of quantum chemistry, machine learning, and reactive molecular simulations to investigate REE coordination, separation, and interfacial processes, while developing predictive computational tools that bridge atomistic mechanisms and experimentally observable properties.

This position offers exceptional opportunities for cross‑disciplinary collaboration, scientific workshop organization, and conference attendance.

Education/

Experience:

Ph.D. in Chemistry, Physics, Materials Science, Chemical Engineering, or a related field completed within the last five years.

• Experience with first‑principles electronic structure methods, including DFT and/or TD‑DFT.
• Experience performing atomistic simulations of molecular and/or condensed‑phase systems.
• Experience with machine learning, data science, uncertainty quantification, or surrogate modeling for chemical systems.
• Demonstrated ability to work creatively and independently as well as learn and collaborate with experts as part of a multi‑disciplinary team.
• Excellent communication and writing skills, as evidenced by publications, cover letter and interview.

• Experience in separations science, coordination chemistry, and materials discovery.
• Familiarity with molecular dynamics simulations, reactive chemistry, and automated reaction discovery.
• Experience with advanced electronic structure methods such as CASSCF, GW/BSE, relativistic methods, or spin‑orbit coupling treatments.
• Knowledge of spectroscopy simulations, including X‑ray, UV‑Vis, Raman, or IR spectroscopy.
• Experience developing or applying machine‑learning interatomic potentials, reactive neural network potentials, or active‑learning workflows.
• Experience using high‑performance computing platforms and large‑scale scientific modeling.
• Experience with model verification, validation, and uncertainty quantification, integration of simulation and experimental observations, and management of scientific datasets.
• Experience in computer programming using modern computing languages. Programming skills in Python and/or scientific computing environments.
• Demonstrated ability to work independently and with minimum supervision.
• Willingness to work productively on multiple projects.

The work location for this position is onsite and located in Los Alamos, NM. All work locations are at the discretion of management.

• The appointment is for a duration of two years, with the possibility of a third‑year extension based on performance evaluation.
• Candidates may be considered for a fellowship supported by the Center for Nonlinear Studies (CNLS). Outstanding candidates may be considered for a Director’s Postdoc Fellowship or for the prestigious Richard P. Feynman, Darleane Christian Hoffman, J. Robert Oppenheimer, or Frederick Reines Distinguished Postdoc Fellowships.
• For more information about the Postdoc Program, go to https://(Use the "Apply for this Job" box below)..php

• Dr. Sergei Tretiak (serg)
• Dr. Arjen van Veelen (arjen.vanveelen)

Due to federal restrictions contained in the current National Defense Authorization Act, citizens of the People's Republic of China (including the special administrative regions of Hong Kong and Macau), the Islamic Republic of Iran, the Democratic People's Republic of Korea (North Korea), and the Russian Federation, who are not lawful permanent residents, are prohibited from accessing facilities that support the mission, functions, and operations of national security laboratories and nuclear weapons production facilities, which includes Los Alamos National Laboratory.

Position does not require a security clearance. Selected candidates will be subject to drug testing and other…