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What You Will Do The T-4 group (Condensed matter and Statistical Mechanics) in the Theoretical Division at Los Alamos National Laboratory (LANL) invites applications for a postdoctoral position in
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modeling capabilities using advanced statistical methods, including Bayesian optimization, machine learning, and multi-fidelity modeling. A background in a relevant field of physics is preferred (e.g. fluid
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accountability (NMCA) duties and responsibilities focused on statistics. As a MC&A Specialist you will contribute to LANL’s National Security mission by helping to ensure compliance with DOE/NNSA requirements
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quantification, statistics, machine learning, high-performance computing, or data visualization. Ability to obtain a Q clearance, which usually requires U.S. citizenship. Additional Minimum Job Requirements for
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and non-technical personnel. Expertise with statistical analysis and forecasting skills, critical and strategic thinking, planning, and organizing. Strong database and information management systems
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quantification, statistics, machine learning, high-performance computing, or data visualization. Ability to obtain a Q clearance, which usually requires U.S. citizenship. Additional Minimum Job Requirements for
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principles used in nuclear materials measurement technologies and systems; such as radioactive decay processes, interaction of radiation and matter, and radiation detection. Statistical Methods: Demonstrated
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of national security. The work we do at Los Alamos National Laboratory (LANL) matters to our country and the world. The Information Sciences Group (CCS-3) in the Computer, Computational and Statistical Sciences
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variety of technical instructions in narrative. Experience with analytics topics such as simulation, statistical analysis, probability, data extraction, input, and cleansing. Note to Applicants: For full
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conclusions, and develop meaningful and practical solutions. Ability to interpret an extensive variety of technical instructions in narrative.Experience with analytics topics such as simulation, statistical