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) information-theoretic active learning, and c) capturing uncertainty in deep learning models (including large language models). The successful postholder will hold or be close to the completion of a PhD/DPhil in
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with the possibility of renewal. This project addresses the high computational and energy costs of Large Language Models (LLMs) by developing more efficient training and inference methods, particularly
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amenable to therapeutic targeting. This position will involve the application of advanced data science approaches to explore large-scale clinical datasets extracted from electronic health records, with
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O’Brien’s research groups at the Department of Engineering Science (Central Oxford). The post is fixed term for two years and is funded by the EPSRC. The development of large-scale quantum computers will
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respectful and fair for all. Find out more about the benefits of working at the University and what it is like to live and work in the Durham area on our Why Join Us? - Information Page The Role and
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high fidelity models of ice crystal icing accretion and shedding, verifying tools using the wealth of unique experimental validation data generated by researchers at the Oxford Thermofluids Institute
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of working at the University and what it is like to live and work in the Durham area on our Why Join Us? - Information Page The Department The Department of Physics at Durham University is one of the leading
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connected large wind energy system dynamic modelling, control and analysis. In particular, the objective of this research programme is to lay the foundations of a new, model and methodology for Advanced wind
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attached to the project. The successful applicant must hold a PhD/DPhil in a relevant subject. They must have peer-reviewed publications using data science approaches, for example, genetic analysis
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, or similar languages, and proficiency in high-performance computing. You will have experience in large-scale genomic data analysis. You will be able to demonstrate how to organise and prioritise work