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in the areas of Hydrological and Earth System Modeling and Artificial Intelligence (AI). The successful candidate will have a strong background in computational science, data analysis, and process
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compliance, reproducibility, and interoperability across scientific domains. By improving data readiness processes, this role will amplify the potential of AI-driven discovery in areas such as high energy
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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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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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/device models into open-source software tools for integrated system dynamic and transient simulations. Integrate post-processing measures for simulations to help with automation. Deliver ORNL’s mission by
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simulation codes, including computational scaling and efficiency, for hybrid exascale supercomputing systems. Programming model for multicore and heterogeneous architectures such as graphical processing units
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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
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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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within a multi-disciplinary research environment consisting of computational scientists, applied mathematicians, and computer scientists to link models and algorithms with high-performance computing
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, finite volume, and machine learning to solve challenging real-world problems related to structural materials and advanced manufacturing processes. The successful candidate will have experience with