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and communication skills in healthcare. You will use sensor-technology to capture multimodal ‘trace’ data including gestures, speech, workspace spatial layout and manual handling of objects. You will
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Mobile and continuous health monitoring has seen major advancements in recent years. The capabilities of current mobile phones and their built-in sensors have inspired many mobile sensing
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sensors — from accelerometers to acoustic and imaging technologies — and support cutting-edge monitoring platforms that operate continuously for industry partners. Your work will directly inform engineering
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Time series are an ever growing form of data, generated by numerous types of sensors and automated processes. However, machine learning and deep learning methods for analysing time series are much
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-driven environments, and low-power sensor networks in resource-constrained settings. Application domains will be across smart cities, intelligent transportation systems, sustainable infrastructure, and
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engineering and power electronics & energy., underpinned by expertise in electronics, RF, sensors, energy systems, and computing devices—driving real-world applications that fuel innovation. You will also lead
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This project aims to harness big data from ubiquitous smartphone sensors to reduce the impact of road transport on the environment. Specifically, we’ll design novel data modelling and indexing
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-problems concerning: activity capture (incorporating computer vision and sensor information to map and identify changes in the environment); activity representation (modelling of the activity and environment