80 distributed-computing-associate-professor Postdoctoral research jobs at Oak Ridge National Laboratory
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of irradiated ceramics and alloys for tritium technology development using advanced experimental and computational methods. The researcher will perform characterization of model systems using techniques such as
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Requisition Id 17066 Overview: The Computational Hydrology and Atmospheric Science (CHAS) Group within the Computational Sciences and Engineering Division (CSED) at Oak Ridge National Laboratory
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Requisition Id 16984 Overview: We are seeking a highly motivated Postdoctoral Research Associate to conduct research at the intersection of quantum computing and high-performance computing (HPC
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Requisition Id 17075 Overview: We are seeking a highly motivated Postdoctoral Research Associate in Organic Chemistry and/or Critical Materials Separation Science to develop next-generation ligands
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distributed intelligence across the computing continuum. In this role, you will have the opportunity to lead and contribute to cutting-edge research aimed at transforming scientific data management and
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Requisition Id 16930 Overview: We are seeking a Postdoctoral Research Associate to advance the scientific validation of quantum simulations for quantum materials. This work directly supports the
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Requisition Id 17011 Overview: The Nuclear Energy and Fuel Cycle Division (NEFCD) of Oak Ridge National Laboratory (ORNL) is seeking a Postdoctoral Research Associate to assist in the development
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solutions to compelling problems in energy and security. We are seeking a Postdoctoral Research Associate who will support the Manufacturing Energy Efficiency Research & Analysis (MEERA) Group in
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Requisition Id 15603 Overview: The National Center for Computational Sciences (NCCS) at the Oak Ridge National Laboratory (ORNL) is seeking a postdoctoral research associate in the area of HPC
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efforts across scientific systems. Develop and apply federated learning on distributed and heterogenous datasets. Develop more efficient and resilient DP techniques that minimize performance loss while