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/Machine Learning (AI-ML) approaches to meeting this challenge. Possible topics include, but are not limited to: storylines for plausible narratives of regional climate change, novel algorithms for rare
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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 trust and authenticity, perceptions of AI and algorithms in digital information environments, news and technology in everyday life, differences in attitudes to AI between journalists and audiences
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algorithms in digital information environments, news and technology in everyday life, differences in attitudes to AI between journalists and audiences, or experiences and understandings amongst different
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particular to the development and validation of novel computational language models, algorithms, and tools for spoken language-based cognitive tests for low-resource languages, and their integration with
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. Material Optimization: Use optimization algorithms to design FGMs that meet demanding performance criteria like fatigue resistance and durability. Systems Integration: Apply a systems engineering approach to
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Background in probabilistic methods Experience with the application of AI algorithms and probabilistic methods Good programming skills Personal characteristics To complete a doctoral degree (PhD), it is