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A Design Methodology for Embedding Robotics & Automation into Circular Product Development This is an exciting opportunity to undertake industrially linked research in partnership with
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Science), a global leader in marine science, the project will develop scalable, low-cost embedded vision systems to analyze marine biodiversity and detect anthropogenic debris. The core challenge is
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Supervisor(s) 1) Professor James Gilbert, University of Hull 2) Dr Hatice Sas, University of Sheffield Increasing productivity and yield in the manufacture of wind turbine blades is a key priority for the UK offshore wind sector, as set out in the Offshore Wind Industrial Growth...
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This PhD opportunity at Cranfield University invites ambitious candidates to explore the frontier of energy-efficient intelligent systems by embedding AI into low-power, long-life hardware platforms
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of novel composite magnetic materials and package-embedded power magnetic core inductors based on these materials, which will be used to implement high frequency and high efficiency IVRs for HPC applications
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This PhD opportunity at Cranfield University invites candidates to pioneer research in embedding AI into electronic hardware to enhance security and trustworthiness in safety-critical systems
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This PhD opportunity at Cranfield University explores how next-generation AI models can be embedded within resource-constrained electronic systems to enable intelligent, real-time performance
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Electronics: Creating next-generation microwave electronics that balance size, power, and performance for handheld platforms. Signal Processing for Embedded Systems: Designing and optimizing algorithms
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at the intersection of neural engineering, computational neuroscience, biomedical signal processing, and embedded systems design. The project aims to develop a novel electrical nerve-stimulation
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PhD Studentship: Distributed and Lightweight Large Language Models for Aerial 6G Spectrum Management
representations and embedding techniques that allow LLMs to natively interpret spectrum-related information, capturing the unique temporal, spatial, and physical characteristics of 6G signals. Building