202 machine-learning-"https:"-"https:"-"https:" positions at Oak Ridge National Laboratory
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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
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Research Associate to develop, scale, and apply artificial intelligence (AI) and deep learning (DL) models for power grid systems. The successful candidate will contribute to scalable AI workflows for grid
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to solve complex problems including information retrieval/extraction, machine learning/deep learning, and networking Special Requirements: Export control, no clearance: This position requires access
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never stop learning. Deliver ORNL’s mission by aligning behaviors, priorities, and interactions with our core values of Impact, Integrity, Teamwork, Safety, and Service. Promote equal opportunity by
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Requisition Id 16695 Overview: As a Senior AI Architect at Oak Ridge National Laboratory (ORNL), you will operate at the intersection of advanced machine learning, software and systems
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and fixtures using hand and power tools. Duties and Responsibilities: Shape or cut materials to specified measurements, using hand tools, machines, or power saw. Read and comprehend specifications in
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, machine learning, artificial intelligence, and predictive analytics capabilities for advanced manufacturing systems and composite structures. Design and execute experimental validation activities to verify
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informed of class logistics. Use the Learning Management System (LMS) for monitoring registrations, determining class assignments, setting delivery schedules, printing rosters, and verifying training records
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and continuous learning. Stakeholder Engagement & Partnerships: Serve as the external interface for the center: liaise with ORNL counterparts addressing lab-wide computing and data initiatives, build
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modeling and networked biological systems. You will work at the intersection of high-performance computing (HPC), computational biophysics, and machine learning, leveraging leadership-class computing