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the world’s most challenging problems through artificial intelligence and data driven algorithms and systems. CSMD creates the mathematics, artificial intelligence, and architecture-aware algorithms
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learning on large-scale HPC systems Scalable and energy-efficient AI training algorithms Image reconstruction, segmentation, and spatiotemporal modeling High-performance computing for large-scale AI and
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uniting national laboratories, academic institutions and industry partners, the QSC is endeavoring to advance American innovation and global leadership by enhancing the computational robustness, algorithmic
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on creating innovative artificial intelligence algorithms for the trusted visualization of large-scale 3D scientific data. This position resides in the Data Visualization Group in the Data and AI Systems
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travel allowance and access to advanced computing resources. The MMD group is responsible for the design and development of numerical algorithms and analysis necessary for simulating and understanding
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algorithms, capable of distributed learning on high performance and edge computing; The design of architectures/models which accurately capture the complexities of the data, with robust estimates of confidence
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uncertainty quantification. The position comes with a travel allowance and access to advanced computing resources. The MMD group is responsible for the design and development of numerical algorithms and
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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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. 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