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, machine learning, mobile robotics, process control, sensor processing, machine vision, and/or human machine interaction. This position will require working with external partners, corporations, and sponsors
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. The position offers the opportunity to work at the interface of model development, observational data synthesis, and emerging AI/ML methods, in close collaboration with researchers from the SPRUCE (Spruce and
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mentor junior staff on chemical processes and provide guidance on historical processes, prior trials, and lessons learned. Support the development of reports, presentations, and operator aids or guidelines
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(ORNL) is seeking a highly motivated Postdoctoral Researcher with expertise in artificial intelligence and machine learning (AI/ML), remote sensing, Earth and environmental sciences, and the analysis
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various workflow processes. Collaborate with colleagues and internal and external groups to design, test, implement, and maintain system enhancements and services while working within established policies
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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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, 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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and ductile fracture is preferred. You will be expected to collaborate with research staff and industry partners to support certification and qualification efforts for components produced by various
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on Quantum Computers on-premise at ORNL and with QSC collaborators and partners. The QHCP group contributes to QSC and situates these developments in the HPC ecosystem. In particular, staff in the QHPC group
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to improve the effectiveness of quality support. Collaborate with QAD colleagues and organizational partners to share lessons learned, feedback, and effective practices. Balance customer needs with applicable