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We invite applications for a self-funded PhD to explore innovative research in the development of human-centred embodied multi-agent systems that able to compensate and augment human capabilities in
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Join a cutting-edge research initiative developing breakthrough sanitation technologies for global impact. This fully funded PhD or MSc by Research opportunity, sponsored by the Gates Foundation
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Cranfield University and Magdrive, offer a fully funded PhD position under the umbrella of the R2T2 consortium to study the optimisation of their thruster for a kick stage. R2T2 is a UKSA-funded
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This exciting fully funded PhD, with an enhanced stipend of £25,726 per annum (with fees covered), will deliver a comprehensive understanding of micropollutant removal in different types of nature
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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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This fully funded PhD studentship, sponsored by the EPSRC Doctoral Landscape Awards (DLA) offers a bursary of £22,000 per annum, covering UK full tuition fees, the funding only covers the home fee
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exceptionally competitive in today's software development job market. At a glance Application deadline13 Aug 2025 Award type(s)MSc by Research, PhD Start date29 Sep 2025 Duration of award1 year - MSc by Research
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Smart sanitation technology represents a critical intersection of automation engineering, embedded systems, and global health innovation. With 3.6 billion people worldwide lacking access to safely managed sanitation, automated toilet systems equipped with IoT sensors, intelligent controls, and...
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This PhD at Cranfield University explores the development of resilient, AI-enabled electronic systems capable of detecting faults and autonomously recovering from failures in real time. The project
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This self-funded PhD research project aims to advance the emerging research topics on physics-informed machine learning techniques with the targeted application on predictive maintenance (PdM