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training algorithms and AI architecture. Image reconstruction, segmentation, and classification. High performance computing for spatiotemporal data. Major Duties/Responsibilities: Develop foundation AI
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Requisition Id 15253 Overview: We are seeking a Postdoctoral Research Associate who will focus on creating innovative uncertainty quantification and visualization algorithms that enable trusted
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of sparse matrix, tensor and graph algorithms on distributed and heterogenouscomputational environments. Basic Qualifications: A PhD in Computer Science, Applied Mathematics, Computational Science, or related
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advanced sensing and controls algorithms for manufacturing Communicate research results through presentations, reports, conference papers, and peer-reviewed journals Deliver ORNL’s mission by aligning
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validate these distributed intelligence algorithms, enabling breakthroughs in scientific research across DOE domains. The candidate will collaborate with DOE’s SWARM project (https://swarm-workflows.org
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computational models and systems using algorithms and analytics for materials and related physical sciences for a broad range of energy, transportation, and advanced manufacturing applications. Major Duties