233 electrical-machine-"https:"-"https:"-"https:"-"https:"-"https:" positions at Oak Ridge National Laboratory
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Office of Science and DOENNSA Experience in the machine design, fabrication, or operation of complex process related systems including vacuum, electrical, HVAC, structural, process, etc. Demonstration
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fundamental topics in mathematics, electrical science, nuclear physics, chemistry, and instrumentation and control, including types of instruments and control systems, principles of operation, and consequences
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through data-driven modeling and optimization. The successful candidate will work at the intersection of thermal-fluid sciences, control theory, and artificial intelligence/machine learning to advance
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degree with experience in Electrical and Computer Engineering, Computer Science, Mathematics, or a science related field. Proven experience in radar and optics applications. Excellent communication skills
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Requisition Id 17106 Overview: The Advanced Engineering Technologies (AET) Group is seeking a dedicated applied mechanical engineer. This position will involve machine design and process engineering
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as needed. Perform preventative and operational maintenance; repair, oil, and maintain machinery and equipment. Repair and replace defective parts when necessary. Fabricate foundations for machines and
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, patents, journal papers, and conference publications, participate in proposals, and estimate costs. Basic Qualifications: A PhD degree in physics, optical or electrical engineering, nuclear engineering, or
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Requisition Id 16600 Overview: The Grid Systems Hardware (GSH) Group at the Oak Ridge National Laboratory (ORNL) is actively seeking applicants for an electrical technician to help with design and
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and Machine Learning skills. This position resides in the AI Operations Program office within the Application Development Division of the Information Technology Services Directorate. Our AI/ML models
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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