Postdoc: Hydrogen–Metal Interaction Modeling

Sandia National Laboratories; Livermore (CA); On-site; USD 75,000 - 100,000; Full time

Benefits offered by this job

Relocation assistance

DOE security clearance support

Job summary

Sandia National Laboratories in Livermore is seeking a Postdoctoral Appointee to join a multidisciplinary team focused on computational discovery and design of materials with tunable hydrogen–metal interactions. You will develop and apply advanced methods to predict and optimize alloys and intermetallics for hydrogen storage and related applications.

The role emphasizes integrating first-principles simulations with machine learning, high‑throughput workflows, and collaboration with experimental

Qualifications

• PhD in materials science, chemical engineering, physics, or closely related field.
• Ability to obtain and maintain a DOE Q clearance.

Responsibilities

• Perform first-principles calculations, including density functional theory, to study hydrogen–metal interactions.
• Develop computational models for hydrogen absorption, diffusion, phase stability, and transport.
• Apply statistical mechanics and thermodynamic modeling to connect atomistic calculations with experiments.
• Build and deploy machine learning models for materials property prediction and screening.
• Develop robust Python-based workflows for data processing, simulation automation, and analysis.
• Collaborate with experimental researchers and industry partners to guide materials synthesis and testing.
• Communicate progress through technical reports, presentations, and publications.

Skills

DFT calculations

Python programming

Materials informatics

ML workflows

Thermodynamics

Experiment collaboration

Academic publications

Education

PhD in materials science or related

Tools

VASP

Quantum ESPRESSO

GPAW

LAMMPS

pymatgen

ASE

scikit-learn

Job description

Sandia National Laboratories in Livermore is seeking a Postdoctoral Appointee to join a multidisciplinary team focused on computational discovery and design of materials with tunable hydrogen–metal interactions. You will develop and apply advanced methods to predict and optimize alloys and intermetallics for hydrogen storage and related applications.

The role emphasizes integrating first-principles simulations with machine learning, high‑throughput workflows, and collaboration with experimental