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Field
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National Aeronautics and Space Administration (NASA) | Fields Landing, California | United States | 18 days ago
comprehensive analysis simulations using CAMRAD II at Mars aerodynamic conditions Post-processing and analysis of DNS, CFD, or comprehensive analysis datasets Geometry creation and mesh generation for simulations
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, containerization (Docker), Kubernetes API development and web-based analytics tools Systems, Optimization, and AI ML/AI for mobility prediction and optimization Graph algorithms, network science Spatiotemporal
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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | 18 days ago
entanglement on a robust, chip-scale architecture. 2. Background and Relevance to NASA This research directly supports NASA’s mission to develop disruptive technologies for the Integrated Network (IN) and
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areas Biomedical applications, social determinants of health or other demographic health areas Spatial microsimulation, spatially weighted regression, combinatorial optimization or Bayesian network
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performance monitoring, calibration, and instrument benchmarking. Develop, optimize, and standardize experimental and imaging protocols, contributing to improved reproducibility and methodological rigor across
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international professional network between researchers and industry associated with the WASP. Subject description Robotics and artificial intelligence aim to develop novel robotic systems that are characterized
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Rana Adhikari and Lee McCuller (Caltech) and Matt Evans and Nergis Mavalvala (MIT) as well as the Lab’s extensive network of experienced researchers and personnel. Successful applicants will be involved
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network models. Of particular interest are candidates who have a background and/or interest in one or more of the following: optimization and optimal control (esp. optimal control of partial differential
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research and innovation to support education and sustainable development, UM6P boasts a state-of-the-art campus and infrastructure. It has built a robust academic and research network and is committed
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Safety, Reliability and Resilience of AI-based Robotics. The successful candidate will have the opportunity to engage with the RIG network, collaborate with academic and industrial partners, and contribute