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and Prof Paul Shearing. The post is funded through a strategic research partnership and is fixed term for up to 2 years. To support the programme, the post holder will be required to carry out research
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anxiety, to work within the established research programme. Substantial hands-on research and professional experience of working with individuals with mental health difficulties, including first-hand
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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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the performance of lithium ion technologies. To support the programme, the post holder will be required to carry out research on characterisation of battery degradation, with a particular focus on the application
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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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the Department of Engineering Science at the University of Oxford. The post is funded by the Oxford Martin Programme on Circular Battery Economies. It is fixed term up to December 2027. You will undertake
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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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Metabolism (OCDEM) on studies related to circadian rhythms in population health. This post is part of a large, interdisciplinary research programme, offering attractive opportunities to work across
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, calcium imaging, optogenetics and/or behavioural methods. The project is part of a broader research programme designed to use cross-species research to uncover mechanisms for memory in both health and
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explores novel aggregation methods at the intersection of AI safety, computational social choice, and judgment aggregation, aiming to formally integrate multi-stakeholder preferences into AI system design