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, scale and resolution in which in vivo pathways of immune cells can be unraveled. Furthermore, it provides a goldmine for training causal machine learning models to move towards precision medicine
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fully funded PhD research studentship in Physics-Informed Machine Learning for Cardiovascular Medicine. This opportunity is open to UK (Home) candidates only. Project Overview Arrhythmias are disorders
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scholarship in “Unsupervised Machine Learning for Cardiovascular Image Analysis”. This opportunity is available to UK (Home) candidates only. Fully-supervised AI techniques have shown remarkable success in
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insights from geometry and topology to discover new applications of machine learning. Multiple positions may be available. Role Requirements The successful candidate must have a PhD (or close to submitting
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Funding for: UK/Home Students We invite applications for a fully funded PhD research scholarship in “Unsupervised Machine Learning for Cardiovascular Image Analysis”. This opportunity is available
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fully funded PhD research studentship in Physics-Informed Machine Learning for Cardiovascular Medicine. This opportunity is open to UK (Home) candidates only. Project Overview Arrhythmias are disorders
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filled The overarching aim of this project is to find synergies between methods and ideas of modern machine learning and of statistical mechanics for the study of stochastic dynamics with application
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Can We Teach AI to Outsmart Humans in the Werewolf Game—Without Changing the AI Itself? Large Language Models (LLMs) have dazzled us with their ability to converse, code, and create—but they still
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synergies between methods and ideas of modern machine learning and of statistical mechanics for the study of stochastic dynamics with application to the analysis of time series. In particular, the project
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to produce resilient and high-performing models. · PhD in Computer Science, Machine Learning, Mathematics, Physics, Statistics, or a related field Strong track record of applying ML in academic or industry