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operando data related to battery degradation and safety. You will develop and implement advanced deep learning models to analyse multi-modal operando data from accelerated stress testing, with the aim
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biologically-inspired deep learning and AI models (NeuroAI). The computational models we work with include vision deep learning models (including topographical, recurrent, or developmentally inspired models
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expertise in deep learning and representation learning applied to biological data, experience with large-scale multi-omics datasets (such as single-cell and proteomics), and strong programming skills in
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The University of London The University of London is both the UK’s largest provider of international distance and online learning and the convenor of a federation of 17 renowned higher education
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future. Fueled by curiosity and a deep sense of duty, they contribute invaluable insights to research and teaching, enriching our society. Are you inspired and driven by the desire to make a meaningful
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knowledge, research skills and interests in deep learning and large language models to work within established research programmes and contribute ideas and solutions. You will also have the ability
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future. Fueled by curiosity and a deep sense of duty, they contribute invaluable insights to research and teaching, enriching our society. Are you inspired and driven by the desire to make a meaningful
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future. Fueled by curiosity and a deep sense of duty, they contribute invaluable insights to research and teaching, enriching our society. Are you inspired and driven by the desire to make a meaningful
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future. Fueled by curiosity and a deep sense of duty, they contribute invaluable insights to research and teaching, enriching our society. Are you inspired and driven by the desire to make a meaningful
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turbines represented using an actuator-line approach, assess the applicability and limitations of reduced-order models in predicting turbine performance, and develop machine-learning surrogate models capable