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DPhil students, manage data analysis pipelines, and contribute to publications and grant writing. This post is ideally suited to someone aiming to secure a long-term fellowship and build an independent
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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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to determine the activators of inflammation in atherosclerosis. You will identify and develop suitable techniques, and apparatus, for the collection and analysis of data (e.g. flow and mass cytometry, confocal
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people to co-produce research and outputs. About You You will have or be close to the completion of PhD/DPhil/DClin or other professional doctorate degree, together with relevant experience and sufficient
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educators, to give young children a voice. About You You will have or be close to the completion of PhD/DPhil/DClin or other professional doctorate degree, together with relevant experience and sufficient
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use computational approaches to mine natural biodiversity in gene sequences to identify engineering targets to increase lipid content and enhance the water use efficiency. The project will make use
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on and defensive mechanisms for safe multi-agent systems, powered by LLM and VLM models. Candidates should possess a PhD (or be near completion) in Machine Learning or a highly related discispline. You
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Postdoctoral Research Associate in Forest Resilience, Climate Change, and Human Health in the Amazon
, epidemiology, and socio-environmental modelling. To be considered a successful candidate; A PhD degree in Ecology, Biodiversity analyses, Environmental Science, Remote Sensing, Epidemiology, Data Science, or a
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becomes essential. This project will focus on building a comprehensive digital twin of a future quantum computer to investigate how classical subsystems scale and interact, and how this scaling impacts
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into real-world settings. You will be responsible for developing machine learning and AI algorithms for a range of data and applications (e.g. natural language processing, multivariate time-series data