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successful candidates will be working with a team of researchers on a range of topics, including artificial intelligence, RF sensing and communications, multimodal UWB RF signal data analysis, and wireless
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recommendations and learn from experience to improve wireless network energy efficiency. The research combines large language models, multi-agent systems, reinforcement learning and knowledge evolution
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areas such as PLLs and clock generation, data converters (e.g., ADCs), and other wireline and wireless applications. 2. Previous experience in IC tape-out, silicon bring-up, and chip testing
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: wireless networks/communications, machine learning/vision, intelligent transportation systems, intelligent sensing/localization, or signal processing. In line with our Athena SWAN ambitions we
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sensing and communications, multimodal UB RF signal data analysis, and wireless sensing network architecture design and optimisation. It is envisaged that the researcher will be located at University
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Telecommunication Research (CTR) at the Faculty of Natural, Mathematical & Engineering Sciences (NMES) has a long history of performing world-class research in wireless communication research. CTR was
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Telecommunication Research (CTR) at the Faculty of Natural, Mathematical & Engineering Sciences (NMES) has a long history of performing world-class research in wireless communication research. CTR was