34 machine-learning-"https:"-"https:"-"https:"-"https:" positions at NEW YORK UNIVERSITY ABU DHABI
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that the candidate has prior research experience in one or more of the following research topics: Free space optical communication Visible light communication DSP for coherent optical communication Machine learning
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. Kyriakopoulos seeks to improve the autonomy of Field Robotic systems by fusing control theoretic and machine intelligence approaches. Formal models are directly applied in real experimental facilities. Marine
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-related data. The ideal candidate must have a background in database management, neuroimaging and/or genomics data analytics, and machine learning and artificial intelligence applications. The candidate is
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MIMO communications Analog, digital and hybrid beamforming architectures Reconfigurable intelligent surfaces Machine learning for wireless communications Hardware-constrained signal processing
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to discuss project developments and thus learn from, support, and brainstorm with their peers in diverse disciplines. Finally, Fellows will submit a brief narrative report of their fellowship activities
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violence victim status, ethnicity, familial status, gender and/or gender identity or expression, marital status, military status, national origin, parental status, partnership status, predisposing genetic
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program is an extension of this effort and will bring together scientists and artists to collaborate, communicate, interact, and learn, promoting the creative thinking that drives innovation. The chosen
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expertise in these areas is highly encouraged. The selected candidate will work on cutting edge technologies in an excellent research environment, with a potential to work with a Quantum Computer through our
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learning theory to join the research team of Prof. Muhammad Umar B. Niazi. The position focuses on the design and implementation of incentive mechanisms for sociotechnical and cyber-physical-human systems
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., 2019; Pedersini et al., 2023). We combine ophthalmological, neuroimaging and behavioral data, and incorporate deep learning methods to facilitate biomarker discovery and enhance predictive power. As a