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Postdoctoral Research Associate - Nuclear Data Evaluation
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- The Materials and Physical Data group (XCP-5) in the Computational Physics Division at Los Alamos National Laboratory (LANL) is seeking 1-2 highly motivated post-doctoral candidates in the area of nuclear data evaluation, with emphasis on uncertainty quantification and application of artificial intelligence (AI) and machine learning (ML).
- The Materials and Physical Data group (XCP-5) in the Computational Physics Division at Los Alamos National Laboratory (LANL) is an interdisciplinary group which develops, implements, and validates constitutive models (material strength, damage and failure, etc.)
- equations of state (EOS), and physical data libraries including opacities and nuclear cross sections for use in large-scale simulation codes; additionally, some group members collaborate in the design and analysis of small-scale and integral validation experiments for material models and physical data.
- Experience with Python, R, Fortran, C
- Clearance : A candidate with the ability to obtain and maintain a DOE Q clearance is desired, but not required.
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