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efficiency of modern and future high-performance computer systems under various workload characteristics through measurement, modeling, and simulation. Publishing papers in high-quality refereed conferences
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, electrical engineering, mechatronics, robotics, computer engineering, computer science, or a closely related discipline. Working knowledge of machine learning and deep learning models, including
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detection, and power grid waveform analytics. You will apply methods traditionally used in wireless communications and signal intelligence — including time-frequency analysis, interference modeling, multi
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crystal material’s growth and characterization. You will perform cutting-edge research on theory and modeling of dynamics in condensed matter. Major Duties/Responsibilities: Development of theoretical
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on defined domains; Fast and scalable algorithms to fit the proposed models to data, with a theory that explains the convergence and success of these techniques; Detailed re-analysis of the performance
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, including a centralized team of designers and the drawing checking team Owns the project’s top-level technical integrated CAD model (non-Conventional Facilities) Manages CAD and PLM/PDM software licenses
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GeoServer and ArcGIS Enterprise. Manage application deployment workflows utilizing Docker. Design database tables and integrate new datasets into existing database models. Use Python to process large
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establish robust data infrastructure supporting foundation model development. This role emphasizes the creation of reusable computational Major Duties/Responsibilities: Design, develop, and validate machine
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the last 5 years Preferred Qualifications: Strong background in experimental systems related to heat and mass transfer systems. Knowledge of CFD tools and analytical modelling is preferred. Experience with
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platforms and autonomous systems, to characterizing global population risk with increasing spatiotemporal clarity, to designing GeoAI models for supercomputer-scale applications, geospatial science at ORNL is