133 machine-learning-"https:"-"https:"-"https:"-"https:"-"https:" positions at Oak Ridge National Laboratory in United States
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research projects. Training & Outreach: Organize workshops, tutorials, and documentation to educate users on best practices. Foster a culture of collaboration, continuous learning, and technical excellence
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machine learning tools for detection, diagnosis, and correction of sensor faults Report results in peer-reviewed publications Deliver ORNL’s mission by aligning behaviors, priorities, and interactions with
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computed tomography (CT) reconstruction, including sparse-view and limited-angle algorithms, and the application of advanced machine learning (ML) and computational imaging methods to scientific and
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Science, Computer Science, Applied Mathematics and Statistics, Electrical and Computer Engineering, Biomedical Engineering, or a related field. Experience with a deep learning framework like PyTorch. Strong
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within the overall machine design. The team membership is cross-functional, including representatives from engineering, operations, manufacturing, quality, reliability, and any other necessary discipline
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, machine learning, geographical information sciences, and many other topics to help frame and solve the above problems on a national and global scale. The successful candidate will contribute to cutting-edge
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communicate expectations, providing visibility of what successful looks like for roles within the group. Establish an environment where learning never stops, honest mistakes are treated as opportunities
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conferences, workshops, and collaborative meetings. Explore integration of advanced computational methods with NMR data analysis, including machine learning approaches for spectral interpretation. Basic
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, management assessments, event reporting, and lessons learned to support business operations and management system performance improvement. Interface with other Battelle and DOE National Laboratories
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, collaboration, inclusion and continuous learning. Stakeholder Engagement & Partnerships: Serve as the external interface for the center: liaise with sponsors (DOE, other federal agencies, industry, academia