10 algorithm-"Prof"-"Prof" Postdoctoral research jobs at Oak Ridge National Laboratory
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solutions to compelling problems in energy and security. The Discrete Algorithms Group at Oak Ridge National Laboratory (ORNL) is seeking a postdoctoral researcher for a two-year position specializing in
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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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Division (MSTD), Physical Sciences Directorate (PSD) at Oak Ridge National Laboratory (ORNL). Examples on areas of research interest include but are not limited to: AI/machine learning algorithm development
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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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on the development and application of machine learning algorithms in areas such as surrogate modeling for physical systems, data assimilation, and scientific data reduction. The position comes with a travel allowance
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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
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the readout manufacturer to adapt and refine the high-speed readout electronics and synchronization system for efficient electron detection. Implement and test real-time processing algorithms for high
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PV inverters), synchronous generators, loads, etc. Develop simulation algorithms that enable large-scale simulations. Integrate (or co-simulate) grid component/device models into open-source software
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this role you will work on some of the most challenging scientific problems facing the Department of Energy, creating new algorithms, tools, and technologies to facilitate knowledge discovery. The rate of
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. Understanding of machine learning algorithms (gradient descent, random forests, etc.) and deep neural network architectures (ResNet and Transformers). A broad understanding of machine learning methodologies and