57 postdoctoral-machine-learning Postdoctoral positions at Oak Ridge National Laboratory
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challenges facing the nation. We are seeking a Postdoctoral Research Associate who will support the Quantum Sensing and Computing Group in the Computational Science and Engineering Division (CSED), Computing
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solutions to compelling problems in energy and security. We are seeking a Postdoctoral Research Associate who will support the Signals Collections and Analysis Group in the Nuclear Nonproliferation Division
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toward integration of hydropower with battery storage and other technologies. Computational and analytical skills : Demonstrated ability in selecting and deploying machine learning tools (Random Forest
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-based modeling of hydrological and Earth system processes. The CHAS group conducts world-class research in hydrological and Earth system modeling, large-scale data analytics and machine learning (ML), and
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postdoctoral research associate to advance the state of scientific AI by addressing cross-cutting challenges in data readiness for AI to enable scalable, reproducible AI workflows on leadership-class systems
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Requisition Id 15892 Overview: We are seeking a Postdoctoral Research Associate to conduct advanced materials research focused on the development of cast, additively manufactured, and wrought
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physics (HEP) detectors, neuromorphic computing, FPGA/ASIC design, and machine learning for edge processing. The successful candidate will work with a multi-institutional and multi-disciplinary team
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Requisition Id 16020 Overview: We are seeking a Postdoctoral Research Associate to reside within the Sample Environment and Labs Section, which is part of the Neutron Scattering Division (NSD
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solutions to compelling problems in energy and security. The Environmental Sciences Division of Oak Ridge National Laboratory (ORNL) seeks a creative individual for a postdoctoral research associate position
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Requisition Id 15721 Overview: We are seeking a Postdoctoral Research Associate who will contribute to the development and implementation of novel quantum algorithms for materials simulation, with