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Field
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the capabilities of fully digital Large Intelligent Surfaces. Subject description The research subject for this position is development of distributed processing strategies and algorithms for Large Intelligent
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quantum dots. In particular, based on our recent result in small arrays, we aim at exploiting coherent control of spin qubit in larger arrays to perform quantum simulation or algorithm. Therefore
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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | about 6 hours ago
optimization algorithms Extensive communications protocol design Solid understanding of physical/link layer communications, including synchronization, beamforming, and autonomous rate adaptation Point of Contact
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decoherence dynamics and other effects of quantum-classical correlations in complex fluid solvents. The methodology will be largely based on Lie group methods and structure-preserving algorithms in geometric
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advantage may arise. The focus of this project is to develop techniques that will enable gate-based quantum optimization algorithms to tackle realistic (large-scale, mixed-integer, and constrained) instances
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validation (V&V) techniques for space systems, software and algorithms with a focus on specific challenges of space-borne perception and proximity operations uncooperative spacecraft . Develop novel methods
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efficient algorithms with provable statistical guarantees, using tools from: high-dimensional statistics, optimization, probability theory, etc. These positions would be especially relevant for those with a
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distributed energy resources (DERs). Design & develop optimization algorithms/tools to plan the deployment of DERs such as energy storage systems (ESS), photovoltaic generations (PV), electric vehicle charging
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reliability of robotic systems. In this role, you will design and implement a safety monitoring system for robotic platforms, utilizing advanced algorithmic tools to validate and enhance the performance
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Designing and extending algorithms grounded in probabilistic machine learning Applying statistical techniques to assess robustness and generalization. Development of methods of research, testing and data