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. These studies will include detailed characterisation of molecular weight distributions, degree of crosslinking, thermal-mechanical modelling and microstructural features that influence electrical performance
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with MoniRail Ltd and Durham University. The primary focus will be on designing and implementing deep learning and anomaly detection algorithms to analyse large-scale, real-world sensor data collected
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. Our team brings together deep expertise in software engineering, distributed systems, machine learning, and cybersecurity. We work across disciplines; from healthcare predictive models for urban air
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quality, and real-time AI performance. This research hub, tackles the intricate challenges of cyber-disturbances and data quality in Edge Computing (EC) environments supporting AI algorithms. The role
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groups in the areas of Intelligent Systems, Machine Learning, Algorithms and Complexity, and Programming Languages and Systems. The Department has also made recent appointments in Quantum Computing and
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for the Future of Intelligence (CFI). The candidate will contribute to teaching and lead a research programme in one or more of the following areas: ethical use of machine learning, AI safety, algorithmic
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flow are significantly increased across various new entities such as distributed energy sources. This will lead to additional information and communications requirements, as well as new information
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(PSDM) techniques to reduce wiring complexity, and optimise signal demodulation algorithms for accurate, real-time battery monitoring. The position will be based in the Department of Engineering, King’s
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data analysis code and/or software algorithms with a focus on interfacing with test systems and automation of test measurements. Essential Requirements As part of the application process, you will be
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, characterisation and/or calibration of image sensors. Good understanding of, and demonstrable experience in, writing bespoke data acquisition and data analysis code and/or software algorithms with a focus on