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for wireless radio access design, including semantic communications and novel waveforms, to deliver high-performance and energy-efficient connectivity in the presence of Doppler and delay spread challenges
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), computation (bioinformatics, machine learning, statistical analysis), working with animals (radio-tracking, animal handling/sampling), and deep knowledge of evolutionary biology and gerontology. The Norwich
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processing, or optimisation to turn heterogeneous knowledge (channel/network state, maps and topology, mobility, hardware constraints, and task-level KPIs) into reliable and efficient decisions. The work spans
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. To meet the demands for accuracy and robustness from emerging applications such as urban air mobility and defence, the navigation community is moving toward cognitive, multi-domain solutions that can
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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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autonomous sensing systems. The project requires experience with setting up sensing hardware, software defined radio systems and other lab equipment for data collection in addition to experience of programming