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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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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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, using a questioning attitude, considering hazards for every task,and never stop learning. Align behaviors, priorities, and interactions with our core values of Impact, Integrity, Teamwork, Safety, and
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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
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learning. Align behaviors, priorities, and interactions with our core values of Impact, Integrity, Teamwork, Safety, and Service. Promote equal opportunity by fostering a respectful workplace – in how we
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of quality initiatives, assesses satisfaction, and exchanges feedback and lessons learned. Analyze, interpret, and communicate quality and performance data to management in support of established metrics and
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science, decision science, discrete algorithms, multiscale methods, experimental computing systems, scalable algorithms and systems, artificial intelligence and machine learning, data management, workflow systems
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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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-processing, information extraction, and post-processing using existing SDR frameworks and algorithms Rapidly prototype SDR signal chains and systems through design, programming, hardware integration, testing
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Requisition Id 16016 Overview: Water and energy systems are deeply intertwined, and advancing science at their intersection is critical to the nation's future. We are seeking two Post-doctoral