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practical applications, including solving mathematical reasoning problems. The ideal candidate has a strong background in machine learning and an interest in bridging rigorous theoretical insights with
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well as machine learning techniques, is central to our mission: Development and application of advanced simulation techniques to explore and identify the fundamental structures and mechanisms occurring in
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PhD Studentship: QoE-Driven Agentic AI for Automated Bug Discovery in Video Games (Collaborative Doctorate with Sony Interactive Entertainment) Video games are complex, continuously updated, and
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plasticity platform. Different machine learning strategies will be explored to capture the complex relationships between microstructural features and mechanical responses. In particular, the project will
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projects, collaborate with international partners, and participate in scientific publications, project development, and technology innovation. Researchers will work within multidisciplinary teams addressing
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related field and have previous academic experience in machine learning. The candidate should have a strong background in metrology and medical image processing. Active participation and collaboration
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spectroscopies, as well as magnetic force- and scanning electron microscopy. You will collaborate closely with your theoretical partner in Utrecht, learning from theory to improve optical strategies and design
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communities concerned? This research involves close collaboration with social partners such as the HERStory Art Foundation (Farida Nabibaks), Theater Thalia, and NAKS. As a PhD candidate, you will conduct
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-disciplinary research team and gain training in state-of-the-art AI methods such as Bayesian optimization, active learning, and scientific machine learning. The project involves close collaboration with
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. You will combine technical work on machine learning with qualitative analysis of how AI systems are interpreted and used in organisational decision-making. Join the Human-Centred Computing group