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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 in related mechanical field. Knowledge of machines and tools, including their designs, uses repair and maintenance. Optical laser alignment experience. Knowledge of robotics or mechanical assembly
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experience leading diverse teams. Must be able to learn at a high level the technical area that is supported. Project management skills and experience, plus significant knowledge of project planning tools with
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, and remote-sensing data) to support model benchmarking, parameterization, and uncertainty quantification. Explore and apply AI/ML approaches (e.g., machine-learning emulators, surrogate modeling, AI
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, computer engineering, computer science, or a closely related discipline. Working knowledge of machine learning and deep learning models, including their application within manufacturing environments
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, and remote-sensing data) to support model benchmarking, parameterization, and uncertainty quantification. Explore and apply AI/ML approaches (e.g., machine-learning emulators, surrogate modeling, AI
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Qualifications: BS in a science, engineering, business administration or industrial-organization psychology with a minimum of two years experience. Possess an advanced level of knowledge in office computer systems
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precision parts and instruments. You will be responsible for applying knowledge of mechanics, mathematics, metal properties and layout and machining procedures. Major Duties/ Responsibilities: Program, set
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, assessing hazards for every task, and committing to continuous learning. Other tasks as assigned by management. Deliver ORNL’s mission by aligning behaviors, priorities, and interactions with our core values
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, computer engineering, computer science, or a closely related discipline. Working knowledge of machine learning and deep learning models, including their application within manufacturing environments