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an interdisciplinary research team and contribute to innovative studies using EEG, virtual reality, robotics and computational methods. You will be part of the project 'The Body Positioning System: A GPS for
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following areas: Virtual, Augmented, and Mixed Reality (VR/AR/MR) Cognitive Modeling and Decision Making Motor Learning Artificial Intelligence and Machine Learning Wearable Technologies and sensors Human
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, combined with advanced motion analysis in the laboratory and wearable sensors in daily life. By linking physiological markers of fatigue to movement quality and real-world activity, you will gain new
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translate them into actionable insights for climate control and crop performance. You will work with chlorophyll fluorescence imagers, leaf-level validation sensors, and modelling tools to support
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grid, which our faculty is helping to make completely sustainable and future-proof. At the same time, we are developing the chips and sensors of the future, whilst also setting the foundations
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sensor measurements to embankment responses will be derived and validated using field data. These relationships will provide a framework for translating routinely collected monitoring data into actionable
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study. The research will begin with the analysis of baseline and historical data collected from wayside sensors installed on selected instrumented railway bridges. Building on these insights, an on-board
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climate control to direct crop-centric control. This paradigm shift relies on breakthroughs in microclimate sensing, interpreting crop performance by integrating sensor data at different temporal and
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through a mixture of qualitative, quantitative, and sensor based approaches to assess student experiences. Rather than seeking to “fix” individual students, our project challenges stigma by addressing
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future-proof. At the same time, we are developing the chips and sensors of the future, whilst also setting the foundations for the software technologies to run on this new generation of equipment – which