10 machine-"https:"-"https:"-"https:"-"https:"-"https:" positions at Lawrence Livermore National Laboratory
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Description We have an opening for a Postdoctoral Researcher to contribute to experimental heavy-ion physics, detector development, and scientific machine learning within Lawrence Livermore National
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. Applications area includes but not limited to multimodal SciML models and deep surrogates for various simulations. This position will be in the Machine Intelligence Group in the Center for Applied
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, including the ultra-high-resolution Energy Exascale Earth System Model (E3SM), the machine learning emulators ACE-ERA5 and ACE-E3SM, and the regional Energy Research and Forecasting (ERF) model. The work
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machine learning, reduced-order modeling, or data-driven modeling of physical systems. You will conduct research on the development of fast, trustworthy, and data-efficient surrogate models that
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simulations to investigate deformation mechanisms in FCC and BCC alloys. Develop a machine-learning based methodology to perform dislocation analysis from high energy X-ray diffraction patterns. Develop
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property predictions (ranging from analytical to machine learning surrogate models) in LLNL’s Materials Acceleration Platform that is deployed on LLNL’s High Performance Computing infrastructure. Develop
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interaction. Diagnose and improve global storm resolving models using ground-based and satellite observations and machine learning. Perform modeling tasks using cloud resolving models or large-eddy
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microscopy [TEM]) for elemental and morphological characterization. Employ artificial intelligence and machine learning (AI/ML) tools to analyze and interpret microanalytical image datasets. Apply
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-spectrometric data using statistical and/or machine learning methods. Experience with software development for hardware control, data acquisition, and data analysis in commonly used languages including
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other visible and infrared diagnostics on the machine, as well as operation of advanced characterization tools in a laboratory environment. Regular interaction and close coordination with CFS technical