321 machine-learning "https:" "https:" "https:" "https:" "https:" "U.S" "U.S" positions at Oak Ridge National Laboratory in United States
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ability to deal effectively with a variety of individuals at all levels Must have high level of organization and computer skills, working knowledge of PC, Microsoft Office (Word, PowerPoint, Excel, Access
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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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needs. By leveraging advanced simulations, machine learning, and data-driven insights, the group enables more effective operations aligned with evolving energy demands. The group also develops hydrologic
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) with questions related to this position. Major Duties/Responsibilities: Develop and apply machine learning models (ML) as surrogates for high-resolution process-based hydrologic models. Design and
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, substation, corridor scenarios) Integrate physics-informed machine learning models with signal processing feature extraction Develop prototype software tools for automated waveform analytics and real-time
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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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. 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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strength of ORNL which is the U.S. Department of Energy’s largest Office of Science laboratory. ORNL is home to two user facilities in manufacturing – the Manufacturing Demonstration Facility (https
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Requisition Id 15990 Overview: We are seeking an Instrument technician who will focus on audio-visual (AV) support and personal computer (PC) maintenance. This position resides in
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modeling, machine learning, and automated experimentation. Mentor and support Group Leaders to ensure excellence in research performance, staff development, inclusion, and cross‑disciplinary collaboration