252 algorithm-development-"https:"-"Simons-Foundation" positions at Oak Ridge National Laboratory
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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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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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to earthquakes, landslides, and volcanic activity. In addition to model development, research activities include the design of evaluation protocols that capture domain knowledge and sponsor application
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scientific data Major Duties/Responsibilities: Design and implement advanced AI architectures and workflows for imaging and spatiotemporal data. Develop efficient and scalable training algorithms
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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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the Integrated Building Deployment and Analysis Group in the BTSD, ESTD at Oak Ridge National Laboratory (ORNL). The IBDA group leads the development of innovative methods for residential and commercial whole
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, water, carbon, and materials productivity throughout the U.S. economy and to identify opportunities for improvement. Through the Industrial Energy Efficiency Program, the MEERA Group develops a diverse
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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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. 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