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supervision, are self-motivated and have strong computational and scientific writing skills. We provide a nurturing environment and access to high-dimensional pathogen genome, human mobility, epidemiological
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have completed, or be close to completing, a PhD/DPhil in a relevant quantitative field such as computational social science, computer science, or cognitive science. They will have a demonstrable track
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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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with an international reputation for excellence. The Department has a substantial research programme, with major funding from Medical Research Council (MRC), Wellcome Trust and National Institute
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sciences discipline, you will be self-motivated, imaginative and able to plan and deliver a research project. You will have a PhD (or be near completion) in one of the above disciplines and have experience
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research initiative funded by ARIA, titled Aggregating Safety Preferences for AI Systems: A Social Choice Approach. The project operates at the interface of AI safety and computational social choice, and
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methods suitable for legged systems in physically-realistic simulated environments and on real robots. You should hold or be close to completion of a PhD/DPhil in robotics, computer science, machine
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learning, at the intersection of reinforcement learning, deep learning and computer vision, in order to train effective robotic agents in simulation. You should hold a relevant PhD/DPhil (or near completion
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will have or be close to the completion of a PhD in Neuroscience, Psychology or a closely related discipline. With in-depth knowledge of cognitive and computational neuroscience including motivation
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for data analysis/scientific computing, and excellent decision-making, problem-solving, planning, and organisational skills. Please direct enquiries about the role to Prof Martin Bureau: (martin.bureau