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techniques, with the ability to independently interpret data and assess compound identity and purity. Proven ability to work independently and drive research forward, including identifying problems, developing
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will design and implement differential privacy solutions for large-scale scientific data models in federated learning environments. You will advance privacy-preserving machine learning by developing
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, thermal transport, or related experimental probes, including the effects of instrumental resolution, data reduction, and observable reconstruction. Experience with uncertainty quantification, covariance
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analyzing and interpreting experimental data to drive product innovation, as well as obtaining and calibrating simulation parameters based on laboratory results. Regular interfacing between experimental and
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program: Contribute to the LEGEND-200 data analysis and the development of advanced analysis routines Contribute to the R&D on advanced instrumentation, design, and simulations of the next generation LEGEND
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-efficient building systems, thermal-fluid processes, industrial heating applications, data center thermal management, and other emerging energy technologies. Develop and operate experimental facilities
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) advanced cooling solutions for energy systems; (3) thermal management for electronics and data centers; and (4) separation processes for building environments. Develop experimental setup, problem-solving
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technologies Proficiency in using Excel, Python, R or similar tools for engineering data analysis is preferrable Excellent written and oral communication skills Motivated self-starter with the ability to work
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in high-performance computing and data analytics with applications in a large variety of science domains and NCCS is home to some of the fastest supercomputers and storage systems in the world
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Application-driven Composable Distributed Storage. The candidate will be able to make research contributions in understanding and efficient use of distributed data storage and I/O subsystems for High