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environments with minimal environmental impact. We are recognized nationally and internationally for our excellence in numerical and computational modelling, experimental innovations, our collaborations with
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PhD Position in Theoretical Machine Learning – Understanding Transformers through Information Theory
Transformers are central to many of today’s most successful AI models, from language understanding to computer vision. Yet, their success remains largely empirical, with limited theoretical understanding
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from satellite, aircraft or ground sensors to understand, model and retrieve parameters relevant to the processes driving our atmosphere, biosphere, hydrosphere and cryosphere. About the research project
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. Of particular interest is the investigation of compositional methods for constructing runtime monitors. The candidate will build on the latest advances in formal methods and learning theory, to develop methods