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properties of skeletal muscle during static and dynamic contractions. The student will also participate in early-stage algorithmic work to model muscle architecture and behavior across contraction types. In
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achieve automated data driven optimization (in terms of time and quality) of polishing process parameters by application of machine learning algorithms, leading to a robust, repeatable and fast polishing
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thus including sensing systems, tool condition features selection, algorithms for automated signal preprocessing, feature extraction and decision making based on ML and AI. An integral part of
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for behavioural and security properties; efficient algorithms for model checking, learning and synthesis; improved explainability and safety of machine learning models, e.g. by integrating neural and symbolic
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expertise in autonomous marine systems. The research focus will be on development, implementation and verification of novel algorithms for motion planning and control of autonomous underwater vehicles. You
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degradation modes. Evaluating suitable sensor technologies and data sources for acquiring relevant metrics. Developing tools and algorithms to automatically analyse sensor data, assess asset condition, and
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of solvers for stochastic optimization problems, and test the methods on real-life data. As part of the PhD you will be following advanced courses to extend your skills, implement and test algorithms, and
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interface, and all the way to quantum algorithms and applications. The long-term mission of the programme is to develop fault-tolerant quantum computing hardware and quantum algorithms that solve life
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better and faster decisions when assessing funding applications, ensuring the efficient and unbiased elimination of poor applications? This question can be addressed through training algorithms on past
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(entities) given the rules and the rules given the molecules. The aim of this project is to develop a theory and accompanying algorithms to decide if an abstract system can be instantiated by a concrete