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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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mathematical and computational techniques, it is essential to have experience in mathematical modelling / dynamical systems theory / numerical methods / coding. An ideal candidate would have a PhD, or
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of the grant. A postdoctoral research assistant with a completed or submitted PhD in climate change law / policy will be recruited at 80% with remote working available. (It is intended that this will leave time
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in the research and management of the Computational Materials Discovery group. You supervise and guide students at the bachelor, master and PhD level. You contribute to the teaching activities in
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also have or be close to completing a PhD in any of the following areas as well as the will and commitment to learn relevant topics from the other areas: Statistical and machine learning, mathematical
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work on large-scale understanding of coastal wetlands - primarily mangrove forests and tidal marshes. This will include mapping and modelling of distribution, value, condition, and opportunities
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for more information. About you To be successful in this role, we are looking for candidates to have the following skills and experience: Essential criteria PhD degree in Engineering, Computer
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work on large-scale understanding of coastal wetlands - primarily mangrove forests and tidal marshes. This will include mapping and modelling of distribution, value, condition, and opportunities
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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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criteria PhD in Neuroscience or near to completion* At least one first-author publication in a scientific journal Extensive experience working with mice Extensive experience analysing single-cell RNA