28 postdoctoral-machine-learning Postdoctoral positions at Oak Ridge National Laboratory
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Requisition Id 16723 Overview: We are seeking a Postdoctoral Research Associate with expertise in artificial intelligence (AI) and machine learning (ML) for multiscale physical systems
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, and remote-sensing data) to support model benchmarking, parameterization, and uncertainty quantification. Explore and apply AI/ML approaches (e.g., machine-learning emulators, surrogate modeling, AI
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, and remote-sensing data) to support model benchmarking, parameterization, and uncertainty quantification. Explore and apply AI/ML approaches (e.g., machine-learning emulators, surrogate modeling, AI
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. Demonstrated expertise in using machine learning and optimization frameworks in conjunction with FE simulations to assist with component and/or process design is preferred. Excellent written and oral
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(ORNL) is seeking a highly motivated Postdoctoral Researcher with expertise in artificial intelligence and machine learning (AI/ML), remote sensing, Earth and environmental sciences, and the analysis
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machine learning and Bayesian calibration methods to enable multi-scale, multi-physics model development. Complete simulation verification, model validation, uncertainty quantification, and documentation
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, computer science, or engineering within the past 5 years. Previous theoretical and/or computational research experience in tensor networks, Monte Carlo, machine learning or a related field Proficiency in quantum
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Requisition Id 16802 Overview: We are seeking a Postdoctoral Research Associate for the development and application of advanced multiphysics simulations, and machine learning (ML) methods relevant
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),. Familiarity with data analytics, machine learning, digital twin knowledge, or Python programming language. Knowledge of additive manufacturing, process physics, thermodynamics, and/or metallurgy to interpret
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solutions to compelling problems in energy and security. The Learning Systems Group at Oak Ridge National Laboratory (ORNL) seeks a postdoctoral researcher specializing in federated learning and privacy