Postdoc: Atomistic Modeling & ML for Catalysis (Hybrid)

Accreditation Council for Graduate Medical Education; Albuquerque (NM); Hybrid; USD 65,000 - 90,000; Full time

Benefits offered by this job

Hybrid work options

Relocation assistance

Flexible schedule

Professional training

Job summary

Sandia National Laboratories in New Mexico seeks a postdoctoral researcher in density functional theory (DFT) and machine learning (ML) to advance multiscale simulations of reactive systems. You will combine first-principles atomistic methods with ML/AI to accelerate materials discovery.

On any given day you may establish high-throughput DFT workflows, develop ML frameworks integrated with LAMMPS, and collaborate with multidisciplinary teams to publish in peer‑reviewed journals and present at

Qualifications

• PhD in a closely related field is required.
• Ability to obtain and maintain a DOE Q-level security clearance.
• Experience with DFT codes and ML architectures for atomistic simulations.

Responsibilities

• Establish high-throughput DFT workflows for sampling chemical reactions.
• Develop ML/AI frameworks and integrate with MD codes such as LAMMPS.
• Plan, conduct, and analyze atomistic simulations of catalysis in complex materials.
• Formulate research hypotheses and carry out collaborative investigations.
• Present findings at conferences and publish in peer‑reviewed journals.

Skills

High-throughput DFT

ML for simulations

Python

C++

Collaboration

Education

PhD in Materials Science/Physics/Chemistry/Engineering

Tools

VASP

Quantum Espresso

Gaussian

LAMMPS

PyTorch

Job description

Sandia National Laboratories in New Mexico seeks a postdoctoral researcher in density functional theory (DFT) and machine learning (ML) to advance multiscale simulations of reactive systems. You will combine first-principles atomistic methods with ML/AI to accelerate materials discovery.

On any given day you may establish high-throughput DFT workflows, develop ML frameworks integrated with LAMMPS, and collaborate with multidisciplinary teams to publish in peer‑reviewed journals and present at