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especially suitable for someone with strong formal reasoning and data analysis skills who is considering progression to a PhD or further postdoctoral research in AI ethics, social choice theory
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cutting-edge research at the intersection of RL and LLMs. You will also design and run experiments to improve LLM efficiency and sustainability. You will hold a relevant PhD/DPhil or be near completion
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, including research assistants, PhD students and project volunteers. This is an exciting opportunity to contribute to world-leading research while shaping bold, practical solutions for people and planet
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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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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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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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and actively contribute to the wider academic environment of the group. It is essential that you hold a PhD/DPhil (or close to completion) in immunology or a related biomedical discipline and have
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inference attacks, to mitigate privacy leaks in MMFM. You will hold a PhD/DPhil (or be near completion) in a relevant discipline such as computer science, data science, statistics or mathematics; expertise in
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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
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microscopy and bioimaging methods to understand dynamic cellular aspects of ciliary dynein assembly. You should hold, or be close to completion of, a PhD/DPhil in biochemistry, together with relevant