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Field
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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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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
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engineering, and hyperparameter tuning to produce resilient and high-performing models. · PhD in Computer Science, Machine Learning, Mathematics, Physics, Statistics, or a related field Strong track record
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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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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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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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are offering an exciting and ambitious PhD research opportunity to explore different molecules/targets to develop infection-specific radiotracers and navigating their clinical translation. Depending
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are offering an exciting and ambitious PhD research opportunity to explore different molecules/targets to develop infection-specific radiotracers and navigating their clinical translation. Depending
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This self-funded PhD research project aims to advance the emerging research topics on physics-informed machine learning techniques with the targeted application on predictive maintenance (PdM
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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