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environments like health care and environmental monitoring. This PhD project aims to address these challenges by exploring how evolutionary algorithms and reinforcement learning (RL) techniques can be combined
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management of microgrids, battery scheduling, and handling uncertain renewable generation without relying on forecasted data [1]-[5]. Studies reveal that parametric tuning of RL algorithms such as state and
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Museums and Inclusive Heritage Preservation Platform Labour, Creator Economies, and Algorithmic Change AI in the Creative Industries (cross-faculty potential) Independent Cinema Exhibition and UK Screen
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to maximise early outbreak detection. Active intervention: developing decision-making algorithms that recommend effective public-health interventions. Reinforcement learning (RL) provides a natural framework
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behaviour in a practical, real-time monitoring system requires advances in both sensor engineering and behavioural data interpretation. This PhD project aims to develop a next generation environmental
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environments like health care and environmental monitoring. This PhD project aims to address these challenges by exploring how evolutionary algorithms and reinforcement learning (RL) techniques can be combined
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21 Nov 2025 Job Information Organisation/Company Swansea University Department Central Research Field Computer science Physics Researcher Profile First Stage Researcher (R1) Positions PhD Positions
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provide large and complex datasets. By applying advanced pattern recognition and clustering algorithms, the aim is to automatically detect coherent spatial domains. These domains represent regions with
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unit and then pre-processed data used as the input of the deep learning algorithm. The research will employ the SafeML tool (a novel open-source safety monitoring tool) to measure the statistical
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Project Description: This EPSRC-funded PhD project will investigate how next-generation electric and autonomous vehicles can operate as symbiotic agents within the urban ecosystem—intelligently