56 data-mining Postdoctoral positions at Oak Ridge National Laboratory in United States
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Requisition Id 16779 Overview: We are accepting applications for Postdoctoral Research Associate positions in Data Science for Advanced Manufacturing that will focus on the development of next
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Requisition Id 16485 Overview: The Data and AI Systems Research Section within the Computer Science and Mathematics Division at Oak Ridge National Laboratory (ORNL) is seeking a postdoctoral
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data science to develop new methodologies for assessing and improving the quality of components fabricated using advanced manufacturing processes. This position resides in the Manufacturing Systems
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magnets, batteries, and semiconductors from mined resources and electronic waste, as well as separations for bioenergy applications. Develop new research directions and contribute to proposals for external
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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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time-of-flight secondary ion mass spectrometry (ToF-SIMS), scanning electron microscopy (SEM), and X-ray diffraction (XRD). Experience in data reduction of big spectroscopy, mass spectrometry, and image
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Requisition Id 17078 Overview: We are seeking a Postdoctoral Research Associate to join the Data Science and Engineering for Nonproliferation Group in the National Security Sciences Directorate
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Application-driven Composable Distributed Storage. The candidate will be able to make research contributions in understanding and efficient use of distributed data storage and I/O subsystems for High
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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
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universities to address project objectives. Present research results within the project and at national and international conferences, and publish findings in peer-reviewed journals, and datasets in DOE data