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physical laws, or an implicit form of extra data examples collected from physical simulations or their ML surrogates. In medical domains, patient data is typically distributed across multiple hospitals
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. An optimisation tool has been developed that uses a genetic algorithm to optimise the location of BGI taking surface water flood risk reduction and the cost of different interventions into consideration. This PhD
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through theory and simulation and/or experimental design and testing; developing new image reconstruction algorithms for providing more information with less radiation; and applying our techniques
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, coordination, and decision-making algorithms for multiple autonomous agents—such as robots (robotic manipulators, drones, or vehicles)—that work together to achieve common goals in dynamic, uncertain
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integrates machine learning and statistics to improve the efficiency and scalability of statistical algorithms. The project will develop innovative techniques to accelerate computational methods in uncertainty
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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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, localization, and sensing, with a focus on developing next-generation multiple-antenna systems while optimizing overall system performance. As a doctoral student, you devote most of your time to doctoral studies
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student, you will be embedded in the research groups Computational Imaging and Deep Learning (CIDL) and Applied Quantum Algorithms (aQa), part of the Leiden Institute of Advanced Computer Science (LIACS
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learning (ML) for high-fidelity data ‘stitching’. The integration of data from multiple analytical platforms is critical for advancing the understanding of complex biological and chemical systems. This work
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slicing. - Develop advanced AI/ML algorithms and data analytics techniques to automate and optimise exposure requests, adapted to available resources and real-time demand. - Propose and