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for Multi-Agent Decision-Making, https://oceanerc.com ). This timely project will develop statistical and algorithmic foundations for systems involving multiple incentive-driven learning and decision-making
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methods to improve the deployment, adaptation capabilities and safety of robots and critical infrastructures. The developed algorithms will be evaluated on legged robots, wheel-based robots and under
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the deployment, adaptation capabilities and safety of robots and critical infrastructures. The developed algorithms will be evaluated on legged robots, wheel-based robots and under-actuated large-scale
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Innovation (UKRI), focusing on populations with multiple long-term conditions. You will contribute to a social care initiative, developing and testing an AI-informed digital tool to help individuals with
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control laws into Trent gas turbine engines and developed algorithms monitoring fleets of 100s of engines flying all around the world. During the PhD, you will have the opportunity to deeply engage with
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development, human-computer interaction, data analytics, user experience design, remote monitoring systems, energy optimization algorithms, and environmental impact modeling. Human-centric AI-driven sanitation
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input needs, accompanied by a boost in algorithmic development, e.g., multi-modal learning, transfer learning, federate learning, and knowledge embedding, etc. However, a significant motivation of
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Innovation (UKRI), focusing on populations with multiple long-term conditions. You will contribute to a social care initiative, developing and testing an AI-informed digital tool to help individuals with
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tuition fees. This PhD project in the area of autonomy, navigation and artificial intelligence, aims to advance the development of intelligent and resilient navigation systems for autonomous transport
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. An optimisation tool has been developed that uses a genetic algorithm to optimise the location of BGI taking surface water flood risk reduction and the cost of different interventions into consideration. This PhD