33 postdoctoral-machine-learning Postdoctoral positions at Oak Ridge National Laboratory
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Requisition Id 17231 Overview: We are seeking a Postdoctoral Research Associate who will focus on the development, application, and optimization of an active learning workflow for dataset
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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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artificial intelligence for science, knowledge-guided machine learning, and scalable scientific AI workflows. The successful candidate will conduct research at the intersection of machine learning, high
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in at least one of the following areas: vehicle dynamics simulation; modeling and control of connected and automated vehicles; AI or machine learning for transportation; traffic modeling, control
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; (ii) advanced free energy simulation methods (e.g., meta dynamics, umbrella sampling); (iii) development and/or application of machine learning potentials (iv) modeling of molecular reaction, (v) Markov
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science, energy, national security, and health. Our researchers develop scalable machine-learning models, deep-learning architectures, and data-driven methods for platforms ranging from edge sensors and
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. To conduct this work, the successful candidate will use the world's first exascale system, Frontier, and collaborate with leading experts in machine learning, optimization, electric grid analytics, and
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photonic quantum sensing and computing. Experience with control electronics, data acquisition systems, machine learning and AI for control and optimization of experimental apparatus. Experience with vacuum
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spectroscopy. Experience designing custom experimental hardware, vacuum systems, and plasma diagnostics. Experience applying machine learning methods for predictive analysis. Expereince with the Python
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Landscape analysis and modeling, with a focus on training and application of predictive machine learning tools. This researcher will synthesize regional-scale remote sensing imagery and ecological monitoring