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Field
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testing of model-free algorithms for real-time optimization of turbine operating conditions (e.g., yaw set points). Other projects may be assigned by the supervisor depending on skills and technical needs
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and resilience across heterogeneous computational resources while addressing workflow requirements for scientific applications. Validate distributed intelligence algorithms at scale on ORNL's
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evaluating efficient and scalable techniques for systems that process and answer such queries (e.g., query optimization algorithms, adaptive query processing approaches). Conducting this research work includes
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to contribute to cutting-edge research in robot intelligence, machine learning, and AI-driven manipulation. This position offers the opportunity to work on real-world robotic systems and develop novel algorithms
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | 28 days ago
. Description: This opportunity is closed to applicants who are Senior Fellows (5-years or more past PhD). The Goddard Earth Observing System (GEOS) global 4D hybrid Ensemble-Variational (EnVar) data assimilation
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. This involves the development of mathematical models for signal transmission/reception, derivation of performance limits, algorithmic-level system design and performance evaluation via computer simulations and/or
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | 27 days ago
. Description: This opportunity is closed to applicants who are Senior Fellows (5-years or more past PhD). Clouds, in particular the frozen phase, bring about the largest challenge and uncertainties
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, and participate in outreach activities that will be generally, but not exclusively, related to your research topics. You are encouraged to visit the ESA website: https://www.esa.int/ Field(s) of
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-year fellowship-program offers excellent researchers who have recently completed their PhD the chance to continue their research career at CTU. Fellows receive a two year fellowship and become members
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research team working at the intersection of machine learning, algorithmic fairness, human-computer interaction, and responsible AI. The project aims to investigate how bias emerges in data pipelines and AI