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to numerical methods for kinetic equations. Mathematical topics of interest include high-dimensional approximation, closure models, machine learning models, hybrid methods, structure preserving methods, and
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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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modeling, curriculum/active learning, data selection, iterative post-training, safety alignment and guardrails. Foundation Models for Science at Scale: Pretraining, instruction tuning, continued pretraining
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seeking a postdoctoral researcher with expertise in data management, workflow management, High Performance Computing (HPC), machine learning and Artificial Intelligence to enhance our capabilities in making
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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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electronic structure theory (e.g., density functional theory), and machine learning based computational studies of molecular and periodic systems. The postdoc will also work within a multidisciplinary multi
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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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Requisition Id 15358 Overview: Oak Ridge National Laboratory (ORNL) is seeking an ambitious postdoctoral scientist with keen interest in artificial intelligence (AI) / machine learning (ML) and
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, at Oak Ridge National Laboratory (ORNL). This position presents a unique opportunity to develop cutting-edge high-performance computing (HPC) that incorporate machine learning/artificial intelligence (ML
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Requisition Id 15287 Overview: The Manufacturing Systems Analytics (MSA) group at the Oak Ridge National Laboratory (ORNL) conducts applied machine learning, decision science, and multi-modal