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This self-funded PhD opportunity sits at the intersection of several research domains: multi-modal positioning, navigation and timing (PNT) systems, AI-enhanced data analytics and signal processing
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This is an exciting PhD opportunity to develop innovative AI and computer vision tools to automate the identification and monitoring of UK pollinators from images and videos. Working at
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. This project leverages and advances these trends, targeting the development of multi-functional coatings to enhance EV battery safety. This PhD will design and characterise intumescent, dielectric, lightweight
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trust in digital communications and readily bypass conventional security controls. This PhD research proposes to design, develop, and validate a novel, explainable, multi-modal detection framework. By
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technologies. Metamaterials, engineered to exhibit properties not found in naturally occurring materials, offer an innovative pathway to overcome these limitations. By designing intricate periodic or quasi
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Cranfield University invites applications for a PhD funded by Thames Water through the Ofwat Innovation Fund. The studentship covers full Home tuition fees plus a tax free stipend of £24,000 per
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This self-funded PhD opportunity focuses on assured multi-domain positioning, navigation, and timing (PNT), integrating data from space-based, terrestrial and platform-based sources of navigation
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more sensitive and faster cancer imaging. This PhD project will focus on surface functionalisation of metascintillators to optimise their scintillation performance, light yield, timing resolution, and
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critical to ensuring the longevity and safety of fusion reactors. This PhD project focuses on developing an integrated framework that combines cutting-edge computational models, including Monte Carlo
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industries, including transportation, consumer electronics, and industrial automation. This PhD project focuses on the design and optimization of intelligent systems with an emphasis on energy efficiency and