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Vacancies 2x PhD positions in the Mathematical Foundations of Machine Learning on Graphs and Networks Key takeaways The Discrete Mathematics and Mathematical Programming (DMMP) group
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). The field of Machine Learning on Graphs aims to extract knowledge from graph-structured and network data through powerful machine learning models. Designing provably powerful learning models for graphs will
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to 1) Object-attribute compositionality to replace exhaustive data requirements with structured concept learning, 2) Bias detection and machine unlearning to identify and mitigate bias and shortcuts
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hybrid AI (combining machine learning, feature-based modelling, and classical OR); Designing intelligent release, workload control and material planning methods that stabilize flow, improve on-time
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from reactive to proactive. The goal is to increase transparency and trust in the DNS namespace. Key research activities will include applying machine learning and graph-based techniques to uncover
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. Through our bachelor’s and master’s degrees, Professional Learning & Development programmes, and interdisciplinary research themes – including Emerging Technologies & Societal Transformations, Resilience
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become better versions of themselves. At BMS we do this through academic education, fundamental science and societal problem-solving. From Bachelor’s or Master’s degrees and Professional Learning
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solutions for medical challenges via signal and system analysis. The Computer Architecture for Embedded Systems (CAES) group conducts research and education in computer architecture and computing systems with
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of Electrical Engineering, Mathematics and Computer Science (EEMCS) uses mathematics, electronics and computer technology to contribute to the development of Information and Communication Technology (ICT). With
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Interaction, are twofold. Firstly, you will advance our knowledge of what high fidelity support systems, both in general and for marine spatial planning specifically, should offer to support use and uptake