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statistical mechanical theory. Collaborations with internal and external fusion efforts will be strongly encouraged. The successful candidate will be mentored and teamed with staff in the National Center
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LiDAR, IMU, camera, and wheel-odometry data in GPS-denied, low-light environments. Implement LiDAR-based or LiDAR-inertial SLAM, factor-graph or pose-graph optimization, loop-closure validation, drift
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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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storage and analysis solutions (e.g., key-value stores, object or document storage, graph analytics systems) deployed on HPC computational and storage systems. Co-authorship of peer-reviewed publications
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, a proven publication record, and effective interpersonal skills. Preferred Qualifications: Knowledge of graph neural networks and other geometric deep learning approaches for graph-structured
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at the intersection of applied mathematics, computational science, and high-performance computing. The successful candidate will help develop advanced scientific computing methods and deploy them on state-of-the-art
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Requisition Id 17068 Overview: For this role, we are seeking an enthusiastic postdoctoral researcher to further develop their expertise in both lifecycle analysis and technoeconomic analysis for several key U.S. industries. As part of this role, the ideal candidate will be passionate about...
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in condensed matter physics, or a closely related field completed within the last 5 years Extensive experience in neutron and/or X-ray scattering Experience in scattering theory, quantum many-body
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chemistry, radiochemistry, theory, spectroscopy, and materials characterization. This project will develop materials and processing technologies that will result in a transformational improvement in
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Requisition Id 16798 Overview: The Data and AI Systems Research Section/Workflow systems Group within the Computer Science and Mathematics Division at Oak Ridge National Laboratory (ORNL) is