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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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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
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B lymphocytes. Specifically, we investigate how transcription, chromatin architecture, DNA replication and epigenetic features regulate the key processes of antibody somatic hypermutation and class