14 postdoctoral-machine-learning Postdoctoral positions at Oak Ridge National Laboratory in computer-science
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generating fusion energy. This research will focus on the chemical speciation and transport of tritium in the molten salt blankets using ab initio quantum simulations, machine learning potentials, and
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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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, 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 17102 Overview: We are seeking a postdoctoral researcher who will focus on the development and application of separation techniques and fusion materials performance assessment
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Postdoctoral Researcher in the fields of uranium chemistry and nuclear forensics. The role entails performing and leading cutting-edge research on nuclear fuel cycle-related materials with a focus on solid
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Postdoctoral Research Associate - Multifunctional Equipment Integration Energy Conversion Technology
Requisition Id 16999 Overview: We are seeking a Postdoctoral Researcher who will focus on conducting, coordinating, and reporting complex research assignments related to advanced thermal and energy
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monitoring in manufacturing environment Develop modular, extensible workflows for data processing Develop and deploy data analytics, machine learning, and statistical modeling methods for multimodal
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facility in the nation. We are seeking to add to our team an energetic and creative postdoctoral research associate. Major Duties/Responsibilities: Research and develop the next generation of advanced
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solutions to compelling problems in energy and security. The Environmental Sciences Division of Oak Ridge National Laboratory (ORNL) seeks a creative individual for a postdoctoral research associate position
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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