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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
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cannot capture the dynamic chemical changes in the gut. There is therefore a critical unmet need for a real-time, chronic gut monitoring tool to unravel neuroendocrine gut–brain pathways and guide therapy
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hardware demonstrator tested under real environmental conditions, contributing to smarter, more sustainable ecosystem management and supporting statutory obligations for innovative environmental monitoring
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This PhD project focuses on advancing computer vision and edge-AI technology for real-time marine monitoring. In collaboration with CEFAS (the Centre for Environment, Fisheries, and Aquaculture
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Researcher (R1) Positions PhD Positions Country United Kingdom Application Deadline 16 Nov 2025 - 23:59 (Europe/London) Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research
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of discomfort. At Swansea University we can monitor a range of perceptual, physiological and temperature parameters, alongside an array of other physiological monitoring tools to measure energy expenditure, and
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intellectual disability associated with either a rare genetic syndrome or a co-occurring condition such as autism. People with moderate-profound intellectual disability and complex needs are at high risk for
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for an International Doctoral Scholar award. Phase discrimination using resonant ultrasound spectroscopy The microstructures of steel are sensitive to small variations in composition and the conditions experienced
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PhD Positions Country United Kingdom Application Deadline 12 Nov 2025 - 23:59 (Europe/London) Type of Contract Permanent Job Status Full-time Hours Per Week 35 Offer Starting Date 1 Jan 2026 Is the job
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configurations and illumination conditions. Implement and validate device-independent representations. Investigate and apply domain adaptation and transfer learning techniques to develop models that generalize