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supported by COMMLab, 6GSPACE Lab, HybridNetLab, QCILab, TelecomAI Lab, CSAT Lab, our SW Simulators, and our Facilities. For further information, you may refer to https://www.uni.lu/snt-en/research-groups
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learning. Job responsibilities will include: Develop simulation algorithms and software to model challenging gas adsorption behavior in porous materials Develop novel machine learning model for predicting
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The opportunity The University of Liverpool is a key partner in a £14 million initiative (https://tinyurl.com/yc5z768m) to develop a sustainable, next-generation manufacturing facility, using
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. Responsibilities: Develop GPU-accelerated dose calculation and optimization algorithms for adaptive HDR brachytherapy. Integrate real-time adaptive planning capabilities into an in-house treatment planning system
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-guided) Evolutionary trajectory analysis and fitness landscape modeling Integration of predictive algorithms with experimental iteration cycles High-throughput screening and selection platform development
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 3 hours ago
, Bayesian statistics) - Remote sensing theory (e.g., radiative transfer physics; algorithm development) - Remote sensing measurements and instrumentation, including calibration and validation, experience
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routine background checks. Essential Duties and Responsibilities Neuroimaging data collection and management Data analysis and model building Develop advanced deep learning and machine learning algorithms
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National Aeronautics and Space Administration (NASA) | New York City, New York | United States | 17 days ago
climate system and the effect of ice-atmosphere feedbacks (e.g., ice albedo feedback and cloud feedback) on sea ice evolution. Developing radiative transfer algorithms to improve both the physical
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projects, including the flagship EXCELSIOR H2020 Teaming Project (https://excelsior2020.eu/ ), as well as DIGIFARM, NOSTRADAMUS, CERBERUS, and CARBONICA. ERATOSTHENES Centre of Excellence is an autonomous
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algorithms for the evolution of inorganic aerosols in the atmosphere, building upon the research group's efforts in modeling combustion-generated aerosols. These modeling framework will be used to understand