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decision with multiple data sources. One example is to develop the semi-supervised methods and dynamic system interfacing algorithms to produce an automated and real-time information exchange across
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. Assess the build quality of parts generated through control model algorithms. Validate that methodologies developed are transferrable between different LPBF platforms through evaluation of parts generated
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communications and sensing. Skills Essential: C1 Excellent programming, algorithm development and scripting skills C2 Research creativity and strong cross-discipline collaborative ability as appropriate C3
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algorithm development; · THz transceivers for high-frequency communication channel measurement and sensing; · Real-Time Digital Simulator (RTDS) and Solar & Wind Emulator for real-time
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powerful framework for decentralised machine learning. FL enables multiple entities to collaboratively train a global machine learning model without sharing their private data, thus enhancing privacy
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, path finding and routing algorithms, sense of direction, human computer interaction, cognitive navigation, intelligent mobility, and artificial intelligence. Sensor fusion and Signals of Opportunity We