125 learning-"https:"-"https:"-"https:"-"https:" positions at Oak Ridge National Laboratory
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activity levels, isotopic content, review of shipping authorization documents, and coordinating cask loading and unloading operations. Learning will be facilitated by requisite training and working closely
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. Engage with the broader community for computational methods, artificial intelligence and machine learning, and real-world coupled physics applications. Deliver on ORNL’s mission by aligning behaviors
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),. Familiarity with data analytics, machine learning, digital twin knowledge, or Python programming language. Knowledge of additive manufacturing, process physics, thermodynamics, and/or metallurgy to interpret
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, considering hazards for every task, and never stop learning. Additional tasks as assigned by management. Deliver ORNL’s mission by aligning behaviors, priorities, and interactions with our core values of Impact
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integrating human-in-the-loop reinforcement learning approaches. Responsible AI: Exploration of privacy-preserving AI techniques, enhancing AI safety, and addressing vulnerabilities and defenses in Large
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safe operations by raising safety concerns, using a questioning attitude, considering hazards for every task, and never stop learning. Deliver ORNL’s mission by aligning behaviors, priorities, and
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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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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
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collaborate with other groups and divisions to support multidisciplinary R&D activities while learning established ORNL policies, procedures, safety practices, and work methods. Deliver ORNL mission outcomes by
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and approaches to solve complex problems (e.g., information retrieval/extraction, machine learning/deep learning, networking) Experience working with geospatial data and processing workflows and