Postdoc: ML-Driven Atomistic Modeling for Metal Joining

Lawrence Livermore National Laboratory; Livermore (CA); Hybrid; USD 104,000 - 142,000; Full time

Job summary

Lawrence Livermore National Laboratory in Livermore, CA, is seeking a Postdoctoral Researcher to advance atomistic and multiscale modeling of metal joining. You will develop machine-learning interatomic potentials with quantum-mechanical accuracy for large-scale simulations and collaborate with mesoscale and experimental teams.

The position offers a hybrid work arrangement, requires a PhD in a related field, experience with DFT/MD and HPC, and the ability to publish results in peer‑reviewed

Qualifications

• PhD in Materials Science, Condensed Matter Physics, Chemistry, Chemical Engineering, or related field.
• Experience with scientific code development: Python, C++, C, Fortran.
• Experience with electronic structure calculations using VASP, Quantum Espresso, or similar codes.
• Experience with molecular dynamics model development and ML methods for materials science.
• Experience with large-scale atomistic simulations in HPC environments.
• Ability to develop independent research projects through publication of peer‑reviewed literature.
• Proficient verbal and written communication skills as reflected in presentations.
• Self-motivated and able to work in a collaborative, multidisciplinary team.

Responsibilities

• Perform and analyze first principles-based simulations (e.g., DFT, DFTB).
• Develop GPU-enabled MLIP models for intermetallic systems for grain boundary and interface modeling.
• Provide inputs for mesoscale and thermodynamic modeling, including interfacial energies.
• Develop and maintain advanced atomistic simulation codes for model optimization.
• Maintain an organized materials database for ML-driven predictions.
• Document research; write and publish papers and present results at DOE venues.
• Pursue independent but complementary research interests and collaborate across Labs.
• Perform other duties as assigned.

Skills

Python

C++

C

Fortran

Machine learning

High-performance computing

Communication skills

Education

PhD in Materials Science, Condensed Matter Physics, Chemistry, Chemical Engineering, or a related field

Tools

VASP

Quantum Espresso

Python (scientific)

GPU-enabled MLIP

Job description

Lawrence Livermore National Laboratory in Livermore, CA, is seeking a Postdoctoral Researcher to advance atomistic and multiscale modeling of metal joining. You will develop machine-learning interatomic potentials with quantum-mechanical accuracy for large-scale simulations and collaborate with mesoscale and experimental teams.

The position offers a hybrid work arrangement, requires a PhD in a related field, experience with DFT/MD and HPC, and the ability to publish results in peer‑reviewed