57 communication-wireless-security Postdoctoral positions at Oak Ridge National Laboratory
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, demand-flexible, and affordable buildings for the DOE Building Technologies Office (BTO), the Federal Energy Management Program (FEMP), and Office of State and Community Energy Program (SCEP). Major Duties
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environment, safety, health and quality program requirements Deliver ORNL’s mission by aligning behaviors, priorities, and interactions with our core values of Impact, Integrity, Teamwork, Safety, and Service
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solutions to compelling problems in energy and security. We are seeking a Postdoctoral Research Associate who will support the Manufacturing Energy Efficiency Research & Analysis (MEERA) Group in
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resources. Present and report research results and publish scientific results in peer-reviewed journals in a timely manner. Ensure compliance program requirements for environmental, safety, health, and
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solutions to compelling problems in energy and security. We are seeking a Postdoctoral Research Associate who will support the Manufacturing Energy Efficiency Research & Analysis (MEERA) Group in
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Postdoctoral Research Associate- AI/ML Accelerated Theory Modeling & Simulation for Microelectronics
aligning 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 treat one
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choice for employment. These principles are essential for supporting our broader mission to drive scientific breakthroughs and translate them into solutions for energy, environmental, and security
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external stakeholders. 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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with environment, safety, health and quality program requirements. Maintain strong dedication to the implementation and perpetuation of values and ethics. Deliver ORNL’s mission by aligning behaviors
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such as quantization, model pruning, approximate attention (linear and sparse) and proposing new mechanisms for tackling speed, accuracy, as well as energy issues, for large language mode (LLM) inferencing