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the theme of: Artificial intelligence and data science in MLTCs Our research theme embraces the exceptional capacity of Machine Learning (ML) to identify patterns in vast collections of electronic health
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. Artificial Intelligence can be used to mitigate this compromise. The project compromises three steps: Implementation of a numerical transient nonlinear model to predict the stack behaviour in a multi-stack
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will build upon this, looking towards the collective potential of constellations of satellites combined with modern Artificial Intelligence (AI) and data communications. The research programme will
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