AI​/ML Trustworthiness and Simulation Credibility Scientist

AI/ML Trustworthiness and Simulation Credibility Scientist 3/4

Join to apply for the AI/ML Trustworthiness and Simulation Credibility Scientist 3/4 role at Los Alamos National Laboratory

This position will be filled at either the Scientist 3 or Scientist 4 level, depending on the skills of the selected candidate. The selected candidate will contribute to the laboratory's mission to solve national security challenges by applying AI/ML to multiphysics computational modeling and verification, validation, and uncertainty quantification (VVUQ) and assessing the credibility of AI/ML models. The work environment is fast‑paced and involves research, publication, and leadership in multidisciplinary teams.

• Research and apply AI/ML VVUQ techniques to computational problems in turbulence modelling, shock propagation, material strength, and high‑energy‑density physics across LANL codes and simulation workflows.
• Publish results in peer‑reviewed journals and present at well‑known conferences.
• Lead multidisciplinary teams, train, and mentor staff new to VVUQ and AI/ML.
• For Scientist 4 candidates: take a technical or programmatic lead on VVUQ and AI/ML directions and influence LANL AI/ML strategy in multi‑disciplinary, mission‑relevant directions.

• Thorough knowledge and experience applying V&V, UQ, and/or machine learning to physics experiments, theory, or computations; familiarity with deep learning fundamentals is beneficial.
• Experience in numerical modeling, computational physics simulations, and advanced analysis supporting AI/ML insights.
• High‑level independent research in at least one of the following areas: deep learning, AI, simulation, verification, validation, uncertainty quantification, optimization, or inverse problems.
• Programming proficiency in Fortran, C++, Python, or alternative sites such as MATLAB, R, Tensor Flow, or PyTorch.
• Strong teamwork and communication skills; ability to communicate scientific research to peers, management, and decision‑makers.
• Experience mentoring and training students and new staff in computational physics, VVUQ, and ML.
• For Scientist 4: experience leading multidisciplinary computational physics teams and developing applied AI/ML capabilities from early R&D to mature systems.
• Required education:
  Master’s degree in a STEM field plus 6 years of relevant experience (Scientist
  3) or 12 years (Scientist
  4).
• Proficiency in obtaining a Q‑Clearance (US citizenship typically required).

• Experience running simulations on institutional‑level High‑Performance Computing platforms using Slurm or Moab submissions.
• Experience using and/or developing LANL’s Advanced Simulation and Computing Program computational physics codes.
• Experience developing and applying verification, validation, uncertainty quantification, or machine learning techniques to computational physics simulations.
• Experience applying ML and AI methods to computational workflows.
• Familiarity with NNSA’s mission and a national lab research environment.
• Familiarity with simulation visualization, post‑processing, and communication.
• Ability to obtain a Q‑Clearance, which usually requires US citizenship.

Work is onsite in Los Alamos, NM. Position commitment is 1 year. All work locations are at the discretion of management.

Due to federal restrictions, citizens of certain countries who are not lawful permanent residents are prohibited from accessing facilities that support national security missions at LANL.

Applicants must submit a CV/resume and a detailed cover letter addressing how their experience relates to each of the required and desired skills. For specific inquiries, contact Brandon Wilson (bwilson).

Los Alamos National Laboratory is an equal opportunity employer. All employment practices are based on qualification and merit, without regard to protected categories such as race, color, national origin, ancestry, religion, age, sex, gender identity, sexual orientation, marital status, spousal affiliation, physical or mental disability, medical conditions, pregnancy, status as a protected veteran, genetic information, or citizenship within the limits imposed by federal, state, and local laws and regulations.

The Laboratory is also committed to making our workplace accessible to individuals with disabilities and will provide reasonable accommodations upon request.