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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 19 hours ago
Lidar and the Roscoe upper troposphere/lower stratosphere lidar). Additional projects include the development of machine learning and advanced data processing algorithms, and participation in upcoming
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computational algorithm and formulation for generating optimised structure and toolpaths while incorporating the manufacturing constraints. Candidate should have a PhD degree in Mechanical Engineering and strong
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environments like health care and environmental monitoring. This PhD project aims to address these challenges by exploring how evolutionary algorithms and reinforcement learning (RL) techniques can be combined
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-off companies. CONTEXT AND MISSION We are seeking a postdoc to join the Quantum Machine Learning team (QML-CVC) in beautiful Barcelona. The QML-CVC team (https://qml.cvc.uab.es /) is part of
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the consumers have economic benefits. Moreover, these smart charging algorithms will be tested in six demonstration sites, dedicated to assessing the technical and economic feasibility of smart charging light and
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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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applications in astrophysics and/or Earth observation, with particular emphasis on the synthesis, interpretation, and modeling of large datasets. Where to apply Website https://apella.minedu.gov.gr/en/node/5999
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research in machine learning (ML) for applications in High-Energy Physics (HEP). We seek highly qualified candidates with interest and experience in ML algorithms including unsupervised techniques, time
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reliability of autonomous Guidance, Navigation, and Control (GNC) algorithms when subjected to realistic stimuli. This research stems from the legacy of the ERC-funded EXTREMA and MUR-funded COSMICA projects
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School graduates over a thousand students who are ready to take on great ambitions and challenges. For more details, please view: https://www.ntu.edu.sg/eee Our department is looking for a Research