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to slower, longer-term, evolution (e.g. vegetation and morphological change). For some, blue spaces may be perceived as ‘wasted space’, whilst highly engineered systems may be perceived as natural
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the intersection of ecology, machine learning, and sustainable land management, the research will combine field data collection, deep learning model development, and stakeholder co-design to support biodiversity
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to ensuring safe, reliable, and high-performance communications. The development of 6G based AI networks with integrated TN and NTN infrastructures provides new opportunities for UAV tracking
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how individuals make movement and life-history decisions in dynamic agricultural landscapes. A baseline model and dynamic energy budget framework already exist, but require development to incorporate
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GNSS alone leaves systems vulnerable to interference, spoofing, or outages, particularly in dense urban environments. The development of 6G networks with integrated TN and NTN infrastructures provides
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tuition fees. This PhD project in the area of autonomy, navigation and artificial intelligence, aims to advance the development of intelligent and resilient navigation systems for autonomous transport
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an effective and vibrant research culture, founded upon the diversity of activities and knowledge. A tailored programme of seminars and events, alongside our Doctoral Researchers Core Development programme
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. Expected outcomes include: development of novel algorithms that significantly improve predictive accuracy for equipment failure; creation of scalable monitoring systems that reduce operational costs
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the development of specialized hardware architectures capable of efficient, real-time processing. Embedded AI hardware architectures, including neuromorphic processors and low-power AI accelerators
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validated surface functionalisation methods that significantly improve metascintillator performance, accelerating the development of advanced radiation detectors for ToF-PET and enhancing early cancer