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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 research project, part of the Gates Foundation’s global health initiative, involves detailed chemical and biological analysis of liquid and solid waste from innovative toilet systems. Students will handle real human waste samples to develop robust protocols for solid and liquid waste...
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Design and Manufacturing Engineering to Tackle Global Sanitation Challenges - MSc by Research or PhD
Design and manufacturing engineering represents the critical bridge between innovative concepts and real-world implementation, particularly in global sanitation technology where products must be both technically sophisticated and manufacturable at scale. With increasing emphasis on rapid...
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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
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This self-funded PhD research project aims to develop smart sensors based on low-frequency resonance accelerometers for condition monitoring of ultra-speed bearings. The developed smart sensors will