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work on the InteGraL project (“Interpretable Graph-Based Machine Learning”). This Leverhulme Trust funded project is focused on developing alternatives to Graph Neural Networks (GNNs). Its central aim
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candidate should have a good understanding of edge computing systems, use of machine learning techniques (e.g. Deep Learning, Transformers) on resource constrained environments at the edge of a communications
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modelling Financial Engineering AI/Machine Learning Neural Networks Intelligent agents/ Collective Intelligence Big Data Analytics Knowledge of the current status of research in a relevant specialist field
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machine learning approaches, whilst leading a broad range of investigative and analytical activities. Bringing skills in biostatistics and bioinformatics, with knowledge and experience of data simulation