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Argonne National Laboratory · 2 days ago

Postdoctoral Appointee - MSD Computational Materials

Lemont, IL

Full-time

Onsite

Mid, Senior Level

$71K/yr - $118K/yr

0+ years exp

Argonne National Laboratory seeks a Postdoctoral Appointee to perform computational research on materials for thermal and electrochemical interfaces. The successful candidate will integrate first-principles and atomistic simulations with machine-learned interatomic potentials to model reaction pathways, construct atomistic structural models, and collaborate with experimental teams.

EnergySecuritySocial Impact

Culture & Values

No H1B

U.S. Citizen Only

Responsibilities

Model reaction pathways on metal-oxide surface, including adsorption, reactions and diffusion steps

Construct atomistic structural models and compute electronic and vibrational properties

Develop and train neural-network or other machine-learned interatomic potentials to enable large-scale molecular dynamics (MD) simulations with near-DFT fidelity

Perform MD simulations to quantify thermal transport across interfaces and evaluate phonon coupling/phonon scattering mechanisms

Derive design rules relating synthesis to thermal and chemical properties; provide computational guidance to experimental synthesis

Collaborate closely with experimental teams to validate and refine models

Publish results in high-impact journals, present at conferences, and contribute to data sets and code repositories

Qualification

Density Functional TheoryMolecular Dynamics simulationsMachine-learned interatomic potentialsAtomistic modelingHigh-performance computingScriptingData analysisMultidisciplinary teamworkPeer-reviewed publicationsEffective communication

Required

Ph.D. (received within the last 0–5 years or by start date) in Physics, Materials Science, Chemistry, Chemical Engineering, Applied Physics, or a closely related field with a focus on computational materials modeling

Density Functional Theory (DFT) for surfaces and interfaces; experience computing reaction energies/barriers (e.g., NEB)

Proficiency with one or more DFT packages (e.g., VASP) and phonon tools (e.g., Phonopy)

Classical/ab initio Molecular Dynamics (MD) simulations of thermal transport; familiarity with NEMD and/or Green–Kubo approaches using LAMMPS or similar

Experience developing and applying machine-learned interatomic potentials and validating them against DFT

Atomistic modeling of reactions on metal oxides, including electrochemical reactions

Understanding of interfacial thermal transport, thermal boundary conductance, and phonon coupling across interfaces

Strong scripting and data analysis skills; experience with high-performance computing environments and job schedulers

Demonstrated ability to work in multidisciplinary teams and to communicate complex results effectively in writing and presentations

Record of peer-reviewed publications commensurate with career stage

Commitment to Argonne's core values and safe work practices; ability to pass a DOE background check per lab requirements