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University invites applications for a PhD position in Statistics (survival analysis). This 4-year position is part of a research project on the development of new statistical methods for the dynamic prediction
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transparent and intelligible. Although explainable AI methods can shed some light on the inner workings of black-box machine learning models such as deep neural networks, they have severe drawbacks and
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years, practitioners and researchers have realized that predictions made by machine learning models should be transparent and intelligible. Although explainable AI methods can shed some light on the inner
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26 Sep 2025 Job Information Organisation/Company Leiden University Research Field Computer science » Computer hardware Computer science » Digital systems Researcher Profile First Stage Researcher
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of invariants of operator algebras, such as K-theory and cyclic homology; and Developing a mathematical method for passing from numerical Berry curvature to robust topological invariants in a large class of cases
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to develop novel AI methods that make powerful models more transparent, robust, and usable in critical domains such as healthcare and smart industry. You will be part of a large national ‘Perspectief
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. The applicant is expected to have: A MSc or equivalent degree in combined Computer Science and Mathematics programs. Alternatively, Mathematics, Computer Science, Computer Engineering, Electrical Engineering
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related discipline in which chemistry and biology have been combined. independent in performing synthetic organic chemistry. experience with (immune) cells, microscopy imaging methods, and/or cell-based
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, multimodal data, and explainability? This PhD project offers you the chance to develop novel AI methods that make powerful models more transparent, robust, and usable in critical domains such as healthcare and
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conversational AI, paying attention to trust, cultural sensitivity, and affective interaction; Design methods and metrics to evaluate bias, fairness, inclusivity, safety, and emotional responsiveness; Explore