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Los Alamos National Laboratory · 2 days ago

AI/ML Trustworthiness and Simulation Credibility Scientist 3/4

Los Alamos, NM

Full-time

Onsite

Senior Level

$125K/yr - $211K/yr

6+ years exp

Los Alamos National Laboratory is a multidisciplinary research institution engaged in strategic science on behalf of national security. They are seeking a highly motivated scientist to apply AI/ML techniques in verification, validation, and uncertainty quantification for computational physics. The role involves leading research efforts, mentoring staff, and contributing to the laboratory's mission to solve national security challenges.

Security

Growth Opportunities

No H1B

Security Clearance Required

U.S. Citizen Only

Responsibilities

Research and apply AI/ML VVUQ techniques to a variety of computational problems including turbulence modelling, shock propagation, material strength and HE detonation across a variety of computational physics 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

Take a technical or programmatic lead on VVUQ and AI/ML directions

Influence LANL AI/ML strategy in multi-disciplinary mission relevant directions

Demonstrate experience in or working with subject matter experts in numerical modeling, computational physics simulations, development of physics models, and/or understanding of relevant physics and mathematics

Conduct high level independent research in one or more of the following areas: deep learning, AI, simulation, verification, validation, uncertainty quantification, optimization, inverse problems or a closely related focus area

Demonstrate experience working and leading multidisciplinary computational physics teams, including interacting with experimentalists and computational physics code users and developers

Demonstrate independent program development and team building

Qualification

VVUQ techniquesMachine learningComputational physicsDeep learningNumerical modelingProgramming in PythonSimulation workflowsTeamworkCommunicationMentoring

Required

Thorough knowledge and experience applying V&V, UQ, and/or machine learning to physics experiments, theory, and/or computations

Familiarity with deep learning fundamentals is beneficial

Experience assessing the credibility or trustworthiness of AI/ML models is desired

Experience in or working with subject matter experts in numerical modeling, computational physics simulations, development of physics models, and/or understanding of relevant physics and mathematics

Demonstrated an ability to distill results from computational simulations using advanced analysis, including AI/ML

Conducted high level independent research in one or more of the following areas: deep learning, AI, simulation, verification, validation, uncertainty quantification, optimization, inverse problems or a closely related focus area

Familiar with at least one of: Fortran, C++ and/or Python. Alternately experience programming in Matlab, R, TensorFlow or PyTorch may be substituted

Show that you are a team player and can work in scientific team environments

Able to ably communicate scientific research to peers

Ability to publish research in peer-reviewed journals or conference proceedings

Experience mentoring and training students and new staff in computational physics, VVUQ, ML, and professional development

Demonstrate experience working and leading multidisciplinary computational physics teams, including interacting with experimentalists and computational physics code users and developers

Experience communicating VVUQ results to management and decision-makers

Demonstrate independent program development and team building

Experience mentoring staff to be technical and program leaders, professional development, and multi-year development of applied AI/ML capabilities from early to mature R&D

Position requires a Master's degree in a STEM field from an accredited college or university and 6 years of relevant experience or an equivalent combination of education and experience directly related to the occupation for Scientist 3 level

Position requires a Master's degree in a STEM field from an accredited college or university and 12 years of relevant experience or an equivalent combination of education and experience directly related to the occupation for Scientist 4 level

The ability to obtain a Q-Clearance, which usually requires US Citizenship

Preferred

Experience running simulations on institutional-level High-Performance Computing platforms using either 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 machine learning and artificial intelligence methods to computational workflows

Familiarity with and demonstrated interest in NNSA's mission and a national lab research environment

Familiarity with simulation visualization, post-processing, and communication