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prediction to process optimization. The focus of this PhD project is to develop and apply machine learning methods across three interconnected tasks: 3D microstructure characterisation. The student will
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. There will be a strong focus on developing robust methods with mathematical guarantees, focusing on statistical and optimization properties with potential applications to cardiology and medicine. The exact
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, such as heterogeneity of data sources and communication constraints. By leveraging tools from statistical signal processing, machine learning, optimization, and mathematical modeling, the project aims
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. Optimal transport is a key mathematical concept that allows us to understand notions like inference and sampling as dynamic processes of probability distributions. Building on the theoretical insights, we
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, mathematics, applied mathematics, computer science, biomedicine, biotechnology, or another relevant field. Documented experience in programming or quantitative data analysis, for example in Python, MATLAB
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, electrical engineering, engineering physics, applied mathematics, or a related field, or completed courses with a minimum of 240 credits, at least 60 of which must be in advanced courses in areas previously
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dynamics. Particular emphasis is placed on opinion dynamics as well as distributed problems in coordination, optimization, and learning. The research encompasses both theoretical and computational aspects
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of the position. Qualifications Requirements for the Position A Master’s degree or equivalent in bioinformatics, engineering physics, mathematics, applied mathematics, computer science, biomedicine, biotechnology
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departmental duties, up to a maximum of 20 per cent of full-time. Your qualifications You have graduated at Master’s level in Electrical Engineering, Computer Science, or Applied Mathematics, with a minimum of
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algorithms. Our research integrates expertise from machine learning, optimization, control theory, and applied mathematics, spanning diverse application domains such as medicine, energy systems, biomedical