29 machine-learning-postdoc positions at Oak Ridge National Laboratory in computer-science
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analytics, including correlation analysis and machine learning techniques. Preferred Qualifications: Experience with microstructure characterization techniques (SEM, EBSD, TEM, XRD). Experience in mechanical
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Requisition Id 16805 Overview: We are seeking a Computer Scientist or Engineer with a focus on Vulnerability Research who will support the Cyber Resilience and Intelligence Division in the National
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transformative solutions to compelling problems in energy and security. The Enrichment Systems Engineering Section is seeking a Machine Design Engineering Group Leader who will support the Enrichment Science and
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of AI for science, including scientific reasoning, federated & collaborative learning, and reinforcement learning (RL) for self-improving models on leadership-class supercomputers. You’ll help design
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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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, 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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(For postdocs, use [email protected] ) with the position title and number referenced in the subject line. Instructions to upload documents to your candidate profile: Login to your account via
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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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. 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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-impact problems and to shape the future of intelligent manufacturing. Major Duties/Responsibilities: Develop and deploy data analytics, machine learning, and statistical modeling methods for multimodal