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terrestrial networks, non-terrestrial network entanglement distribution. Your profile PhD degree in wireless communications, signal processing, machine/deep learning or a closely related field in Electrical and
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player and great collaborator Strong interest in interdisciplinary work at the interface between neurodegeneration, modeling, screening and machine learning Prior experience in iPSC modelling and CRISPR
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perfecting Spanish in Seville. It’s how Horned Frogs are learning to change the world. Show more Show less Connections working at Texas Christian University More Jobs from This Employer https
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the last three years prior to the application deadline. Experience in some of the following areas is meritorious: AI and machine learning; convex analysis; functional analysis; mathematical statistics
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Details Posted: Unknown Location: Salary: Summary: Summary here. Details Posted: 27-Jan-26 Location: Abu Dhabi Categories: Academic/Faculty Internal Number: 64421 The Division of Engineering at New
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | 4 days ago
measurements in atmospheric field programs. Development and application of new lidar technology and machine learning methods are emphasized. We investigate and interpret observations from multiple sensors
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machine learning technologies in order to provide evidence-based decision support tools in near real time across a variety of thematic domains: disaster risk reduction, sustainable agri-food systems
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inverters to enhance grid flexibility, reliability and stability. • Apply machine learning and AI tools for the battery system health estimation and maintenance prediction and integrate analytics
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Education: PhD in Artificial Intelligence, Bioinformatics, Computer Science, Physics, Engineering, or a related field. Programming: Proficient in Python. Machine Learning: Strong experience with frameworks
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topics: Free space optical communication Visible light communication DSP for coherent optical communication Machine learning and AI-native physical layer design Optical reconfigurable intelligent surfaces