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and data analytics with applications in a large variety of science domains. NCCS is home to some of the fastest supercomputers and storage systems in the world. This position is in the Technology
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strengths in high-performance computing, system architecture, and data analytics with applications in a large variety of science domains. NCCS is home to some of the fastest supercomputers and storage systems
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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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applied mathematics and computer science, experimental computing systems, scalable algorithms and systems, artificial intelligence and machine learning, data management, workflow systems, analysis and
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Simulation & Data Processing: Use and extension of Allpix2 and TCAD-based simulation tools. Generation of large simulation datasets for algorithm training and validation. Integration of simulation with
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solutions for large-scale scientific data models in federated learning environments. You will advance privacy-preserving machine learning by developing efficient techniques that maintain robust privacy
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Department of Energy (DOE). ORNL’s CCP conducts world-class research and development in multi-scale computational coupled physics, large scale data analytics and DL, and model-data integration at the DOE’s
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technical assistance support for industrial sites, and other large energy users, installing electricity and thermal energy generation and storage technologies at their facilities. The MEERA Group actively
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Expertise in machine learning and big data analysis Excellent written and oral communication skills Motivated self-starter with the ability to work independently and to participate creatively in collaborative
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large-scale training and post-training pipelines (including distributed data/compute and evaluation harnesses). Collaborate with domain scientists and external partners; co-develop end-to-end AI workflows