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Soma Skins. The PhD will be part of the wider Somabotics programme that is exploring new kinds of creative interaction between humans and AI, especially robots. You will join a multidisciplinary team of
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-specific alpha-synuclein A30P human mutation, we will employ electrophysiological techniques, RNA sequencing, proteomics, and histochemical analysis. The findings are expected to provide insights into early
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sweat distribution across impairment groups which may inform future clothing design for improved thermoregulation. Additionally, it will explore cooling interventions, using computational modelling
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their property. Methodology: The aim is to apply a newly developed Coupled Human And Natural Systems (CHANS) model to simulate and understand the interactive human behaviours and social dynamics before and during
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In this PhD project, we will develop and implement approaches for estimating the uncertainty in AI predictions of chemical reactivity, to help strengthen the interaction between human chemists and
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In this PhD project, we will develop and implement approaches for estimating the uncertainty in AI predictions of chemical reactivity, to help strengthen the interaction between human chemists and
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deep reinforcement learning framework, which interactively optimises key performance indicators in the form of a human-expert informed reward function. Second, we aim for the integration of low-energy
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to human and environmental interactions across various sectors such as healthcare, education, and urban planning. The primary aim of this project is to develop Multi-Intelligence Agents (MIAs) that combine
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the air-we-breathe, water-we-drink, and food-we-eat. Notably, humans are thought to ingest upto 5 grams per week. Interaction of ingested MNPs with the gut microbiome promotes development of microbial
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decisions related to turbine inspection and maintenance with a human expert [4, 5]. This can be based on a deep reinforcement learning framework, which interactively optimises key performance indicators in