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planning algorithms to re-route or schedule multiple vehicles to minimise the impact on the efficiency and safety. This PhD position is related to a 2-year project funded by SESAR, involving various partners
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electronic converters are required to connect renewable energy sources and energy storage systems to the power network. These converters employ sophisticated control algorithms that must simultaneously achieve
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to apply it in selected poor-resource settings. This project aims to achieve several objectives, including the development of a new AI-algorithm and a paired dataset for comparing how different imaging
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to real-time aerosol sensing for adaptive route planning, and performing post-flight data analysis to link aerosol properties with changes in radiance across multiple wavelengths. We’re looking for someone
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—remains a critical challenge. This project will focus on designing AI-driven cognitive navigation solutions that can adaptively fuse multiple sensor sources under uncertainty, enabling safe and efficient
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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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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