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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
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written and verbal communication skills and will be well prepared for an exciting career development either in academia or industry or ac.
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the operational life of battery-powered devices and reducing the environmental impact of large-scale deployments. Advancements in this area support the development of sustainable technologies across various
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highly attractive to both the tech industry and government agencies. They will gain extensive practical skills in full-stack AI development, from data curation and model training to system deployment and
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the diversity of activities and knowledge. A tailored programme of seminars and events, alongside our Doctoral Researchers Core Development programme (transferable skills training), provide those studying a
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. The research will explore the development of hardware security primitives, embedded trust protocols, side-channel attack mitigation techniques, and tamper detection mechanisms. Additionally, the project will
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the development and validation of diagnostic and prognostic algorithms. Electronic Prognostics Systems: Facilities equipped to assess the health and predict the remaining useful life of electronic components
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of complex metagenomic data. You will also become proficient in lifecycle carbon accounting and data-driven decision-making, all mapped to the Researcher Development Framework at Cranfield University. Regular