AI/ML for Critical Infrastructure Postdoc (National Security)

Los Alamos National Laboratory; Los Alamos (NM); On-site; USD 120,000 - 190,000; Full time

Benefits offered by this job

Relocation assistance

Excellent benefits

Onsite gyms

Job summary

Los Alamos National Laboratory (LANL) in Los Alamos, NM, seeks a scientist with demonstrated ML expertise to advance data-driven modeling for complex systems. You will contribute to surrogate modeling, uncertainty quantification, and probabilistic prediction while pursuing innovative research directions.

Qualifications include a PhD in a related field and strong publication record, with the ability to obtain a DOE Q clearance.

Qualifications

• PhD in a related field within the past 5 years is required.
• Demonstrated experience in ML, modeling, and uncertainty quantification.

Responsibilities

• Lead research in ML and data-driven modeling for complex systems.
• Develop new research directions beyond existing methods.
• Collaborate with interdisciplinary teams to advance national security science.

Skills

Machine Learning

Data-driven modeling

Scientific computing

Statistical methods

Publication record

Surrogate modeling

Emulation

Data assimilation

Uncertainty quantification

Probabilistic prediction

Multi-modal data integration

PyTorch

JAX

Python

NumPy/SciPy

Security clearance

Education

PhD in Electrical Engineering/CS/Physics or related field

Tools

PowerWorld

Pandapower

MATPOWER

PowerModels

GasModels

ns-3

Git/version control

Python

Job description

Los Alamos National Laboratory (LANL) in Los Alamos, NM, seeks a scientist with demonstrated ML expertise to advance data-driven modeling for complex systems. You will contribute to surrogate modeling, uncertainty quantification, and probabilistic prediction while pursuing innovative research directions.

Qualifications include a PhD in a related field and strong publication record, with the ability to obtain a DOE Q clearance.