Postdoc: AI-Driven Materials Science & Quantum Chemistry

Los Alamos National Laboratory; Los Alamos (NM); On-site; USD 65,000 - 95,000; Full time

Benefits offered by this job

PPO or HD medical insurance

Dental and vision insurance

Life and disability insurance

Paid childbirth and parental leave

401(k) with matching

Tuition assistance

Flexible schedules and PTO/holidays

Onsite gyms and wellness programs

Relocation packages

Job summary

Los Alamos National Laboratory is seeking postdoctoral researchers to join a multi-disciplinary team focusing on integrated molecular simulation, molecular design, and optimal experiment design for f-element materials. The role intersects quantum chemistry, machine learning, and agentic-AI across lanthanides/actinides separation.

The successful candidates will collaborate with theoretical and experimental scientists to advance AI-driven workflows, with a two-year appointment and potential

Qualifications

• Broad experience applying ML/AI to molecular or condensed-phase systems.
• Development of AI/ML scientific workflows for computational chemistry or materials science.
• Strong background in density functional theory (DFT) and electronic structure methods.
• Experience with atomistic simulation methods including MD, MC, free-energy calculations.
• Ability to work independently and in multi-disciplinary teams; excellent communication.

Skills

ML workflows

Data science

Uncertainty quantification

Surrogate modeling

First-principles methods

Molecular dynamics

Team collaboration

Communication

Education

Ph.D. in Chemistry/Physics/Materials Science/Engineering

Job description

Los Alamos National Laboratory is seeking postdoctoral researchers to join a multi-disciplinary team focusing on integrated molecular simulation, molecular design, and optimal experiment design for f-element materials. The role intersects quantum chemistry, machine learning, and agentic-AI across lanthanides/actinides separation.

The successful candidates will collaborate with theoretical and experimental scientists to advance AI-driven workflows, with a two-year appointment and potential