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at the APS, integrating x-ray optics and wave propagation models with realistic sample simulations based on dislocation dynamics and molecular dynamics of relevant materials. Significant attention needs
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A postdoctoral position on exascale atomistic simulations, AI/machine learning and data analysis of ferroelectric devices is available immediately at the Center for Nanoscale Materials (CNM
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real-time simulation platforms. Knowledge with designing, modeling, or hardware prototyping of power electronic converters. Proficiency in Python and/or C. Ability to work both independently and
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microscope, as well as electrostatic beam blanker or ultrafast pulser in electron microscopes. Proficient in data analysis and modeling, with experience using Python and other programming or simulation tools
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information Ability to model Argonne’s Core Values: Impact, Safety, Respect, Integrity, and Teamwork Desired skills, knowledge and abilities: Experience with large-scale molecular dynamics (MD) simulations
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years. It has developed the GREET® (Greenhouse gases, Regulated Emissions, and Energy use in Technologies) model for estimating energy use, air emissions, and water consumption on a life-cycle basis for
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including engineering, economics, and environmental science. Experience developing mathematical or computational models for simulation and optimization of energy/economic systems in ASPEN Plus® and/or Julia
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We are seeking a highly motivated Postdoctoral Appointee with a strong background AI/ML specifically in the development and application of Large Language Models (LLMs) tailored for scientific use
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to solve challenging problems in the microelectronics area. Note: Synthesis of bulk materials, first-principles simulations/modeling, and organic or bio-related areas are not in consideration
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). Knowledge of the Multiphysics Object-Oriented Simulation Environment (MOOSE) framework. Experience in computational modeling of advanced reactor designs including both fission and fusion systems. Knowledge