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include data compression and reconstruction, data movement, data assimilation, surrogate model design, and machine learning algorithms. The position comes with a travel allowance and access to advanced
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science, decision science, discrete algorithms, multiscale methods, experimental computing systems, scalable algorithms and systems, artificial intelligence and machine learning, data management, workflow systems
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. Experience with machine learning and data-driven approaches to diagnostic signal processing and real-time control. About ORNL: As a U.S. Department of Energy (DOE) Office of Science national laboratory, ORNL
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analysis, as well as propose and collaboratively develop new avenues of application for these techniques. Other areas of focus include applications of machine learning and artificial intelligence tools
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management, workflow management, High Performance Computing (HPC), machine learning and Artificial Intelligence to enhance our capabilities in making AI-ready scientific data. As a postdoctoral fellow at ORNL
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computational physics, computational materials, and machine learning and artificial intelligence, using the DOE’s leadership class computing facilities. This position will utilize methods such as finite elements
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Requisition Id 15885 Overview: We are seeking a Postdoctoral Research Associate – Simulation and Machine Learning for Composite Manufacturing who will focus on developing physics-based simulation
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a unique opportunity to develop cutting-edge high-performance computing (HPC) that incorporate machine learning/artificial intelligence (ML/AI) techniques into visualizations, enhancing the efficiency
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Sciences Directorate, at Oak Ridge National Laboratory (ORNL). This position presents a unique opportunity to develop cutting-edge high-performance computing (HPC) and machine learning/artificial
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or PhD in Computer Science, Computer Engineering, Cybersecurity, or related fields with 2-4 years of experience. Proven experience architecting and implementing complex distributed systems tailored