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creation, fundamental questions of epistemic risks and illusions of understanding of scientific knowledge arise. This position will help us to advance our knowledge about how humans learn to trust AI systems
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illusions of understanding of scientific knowledge arise. This position will help us to advance our knowledge about how humans learn to trust AI systems, including ways in which they can fruitfully critique
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. This position will help us to advance our knowledge about how humans learn to trust AI systems, including ways in which they can fruitfully critique and challenge them. The successful candidate will work closely
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event sampling or ensemble boosting, and the development and use of hybrid climate models combining physics-based and ML components. About the LEAD AI fellowship programme LEAD AI is the University
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for plausible narratives of regional climate change, novel algorithms for rare event sampling or ensemble boosting, and the development and use of hybrid climate models combining physics-based and ML components
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for plausible narratives of regional climate change, novel algorithms for rare event sampling or ensemble boosting, and the development and use of hybrid climate models combining physics-based and ML components