28 computer-algorithm Postdoctoral positions at Oak Ridge National Laboratory in United States
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, data assimilation, surrogate model design, and machine learning algorithms. The position comes with a travel allowance and access to advanced computing resources. The MMD group is responsible
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to Computational Methods for Data Reduction. Topics include data compression and reconstruction, data movement, data assimilation, surrogate model design, and machine learning algorithms. The position comes with a
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for the design and development of numerical algorithms and analysis necessary for simulating and understanding complex, multi-scale systems. The group is part of the Mathematics in Computation (MiC) Section
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. Eventually, we aim to map these algorithms on to energy-efficient emerging devices. In addition, you may also explore applying LLMs to drive multimodal models in scientific domains towards deep reasoning. As a
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computing resources. The MMD group is responsible for the design and development of numerical algorithms and analysis necessary for simulating and understanding complex, multi-scale systems. The group is part
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Oak Ridge National Laboratory, Mathematics in Computation Section Position ID: ORNL-POSTDOCTORALRESEARCHASSOCIATE3 [#27208] Position Title: Position Type: Postdoctoral Position Location: Oak Ridge
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Requisition Id 15448 Overview: We are seeking a Postdoctoral Research Associate who will focus on creating innovative artificial intelligence algorithms for the trusted visualization of large-scale
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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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. Basic Qualifications: A PhD degree in civil, chemical, or environmental engineering. A minimum of 2 years of experience in the use of Python for programming of data analytical models and algorithms
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Development of imaging and sensing systems for data collection Support the implementation of various algorithms for computation at the edge Design experiments for parameter space exploration Publish research in