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Science and Technology (CST) at the University of Cambridge. The goal of this PhD programme is to launch one "deceptive by design" project that combines the perspectives of human-computer interaction (HCI) and
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across diverse socio-contexts. Applications include healthcare and emotional recognition, addressing critical challenges in human-machine interaction and personalised care. The successful candidate will
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on human-environment interactions in freshwater ecosystems. The studentship covers fees and stipend for a home (UK) student. There is an urgent need for novel freshwater quality monitoring solutions to help
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to the perception of animacy when interacting with objects and people using videos (behaviour, fMRI, and MEG), 3) determine to what extent these brain representations and dimensions change when humans are immersed in
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, modifying gel-forming capabilities), virus-host interactions, infection and cell-cell interactions. We hypothesise that alterations in proteins related to post-translational mechanisms including FUT2
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to train tomorrow’s leaders in earth and environmental science. For further details about the programme please see http://nercgw4plus.ac.uk/ For eligible successful applicants, the studentships comprises
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researchers in Cranfield Environment Centre and the Connected Waters Leverhulme Doctoral Programme, which focuses on human-environment interactions in freshwater systems. They will benefit from a lively and
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. The studentship is funded by the Leverhulme Trust through the Connected Waters Leverhulme Doctoral Programme. Urban blue networks, including rivers, canals and wetlands, are dynamic systems that shape how cities
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the most energy‐intensive infrastructures in modern economies, with their demand projected to rise sharply as digitalisation, artificial intelligence (AI), and cloud computing expand. This growth presents
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personalisation of social/companion robot for long-term engagement Expanding the applicability of the social robot, Kaspar, to diverse user groups Machine Learning for Human-Robot Interaction Neuroethology