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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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sleep patterns, gaining insights into sleep-related issues, and personalised sleep health management. However, the dynamic nature of sensor networks caused by frequently adding and removing nodes has
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Fixed term – until 31/3/2026 Full time - 37 hours per week Closing date 27/05/2025 at 23:30 Sheffield Hallam University is recruiting for a Researcher in Advanced Sensor Technology to support the
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This fully funded position focuses on the development of sustainable ingestible medical devices. Most current ingestible devices are single-use, plastic-encased systems with embedded electronics that are flushed post-use. The successful candidate will investigate new manufacturing...
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are looking for a researcher to drive the preparation and analysis of new and existing large-scale wearable sensor datasets. You will be an integral member of the wearables group based at Oxford, led by Aiden
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are looking for a researcher to drive the preparation and analysis of new and existing large-scale wearable sensor datasets. You will be an integral member of the wearables group based at Oxford, led by Aiden
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of experience in the development of sensors for healthcare applications; Dr Diganta Das; Stephanie Edwards and Andrew Peers. Loughborough University has an applied research culture. In REF 2021, 94% of the work
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food fouling removal during CIP processes and integrate in-line sensors to assess water quality for reuse. Since most foods contain fluorophores that fluoresce under UV light, detecting this fluorescence
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systems. The study focuses on the fundamental design, analysis, optimisation, and investigation of nonlinear dynamics in MEMS sensors, with a particular emphasis on enhancing sensitivity through
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studentship will work with conservation charities and citizen scientists to develop and validate innovative origami-paper eDNA sensors for the rapid detection of chemical and microbial contaminants in river