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characterization, mechanical testing, 3D microstructural analysis, finite element simulations, atomistic modeling, and thermal transport measurement techniques to advance mechanistic understanding and predictive
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standard (version control, unit testing, continuous integration, etc.). Experience in the development of large-scale physics simulation codes, including coupling of multiple codes, and an understanding
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post-doctoral research associate to simulate amorphous materials and crystallization reactions using atomic-scale simulations. As a post-doc, you will utilize high performance computing and rare event
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reproducible AI practices. Heterogeneous Data Integration: Address challenges in reconciling experimental, simulation, and observational datasets with varying resolutions, data fidelity, and sampling rates
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Postdoctoral Research Associate- AI/ML Accelerated Theory Modeling & Simulation for Microelectronics
that can incorporate multi-scale computational simulations to aid with data fusion across multiple modalities of experiments with the final goal of discovering novel materials phenomena or even new materials
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computing resources. The MMD group is responsible for the design and development of numerical algorithms and analysis necessary for simulating and understanding complex, multi-scale systems. The group is part
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travel allowance and access to advanced computing resources. The MMD group is responsible for the design and development of numerical algorithms and analysis necessary for simulating and understanding
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experimentally validating simulations efforts for quantum spin systems. This position resides in the Correlated Electron Materials Group in the Materials Science and Technology Division, Physical Sciences
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for simulating atomic nuclei, as well as preparing data and using machine learning models for investigating how the properties of atomic nuclei connect to fundamental questions in physics, such as constraining
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Proficiency in the use of industry standard modeling and simulation tools, such as spreadsheet-based process cost modeling, input/output modeling, and commercially available life cycle analysis tools such as