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learning architectures including generative models, particularly for sequence or structural data (e.g. transformers, graph neural networks) Proved experience in working independently and as part of a
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datasets Proficiency in Python for data science and machine learning Possess sufficient breadth or depth of specialist knowledge with deep learning architectures including generative models, particularly
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architectural choices for neural networks. This project will be in collaboration with Prof. Mark Sandler from the Centre for Digital Music – a world-leading research centre in the field of AI for Music and Audio
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. Desirable criteria Track record of interdisciplinary collaboration. Familiarity with cognitive architectures or agent-based modelling frameworks. Ability or potential to contribute to the development
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of shut-offs – in European and US cities in relation to the changing political economy of the welfare state, social infrastructures, and public service provision. Under the direction of Prof Meehan as
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in the heart of the City of London and is close to the Barbican Art and Music Centre and St Paul’s Cathedral. About Queen Mary At Queen Mary University of London, we believe that a diversity of ideas
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persistence of household water insecurity – specifically problems in access to running water and the rise of shut-offs – in European and US cities in relation to the changing political economy of the welfare
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Square Campus in the City of London and within the world-renowned William Harvey Research Institute at Barts and The London School of Medicine, Queen Mary University of London (QMUL). The appointed person
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holds Crainio, a spin off company from City University of London. Crainio sets out to revolutionise how to measure ICP by developing a non-invasive, inexpensive measurement instrument that uses a simple
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research in neuro-symbolic AI, with a focus on using generative AI and prompt engineering as a method to engineer knowledge graphs one can trust. This includes the design of algorithms and architectures, but