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, regression models or machine learning. Applicants from clinical hepatology with experience in the above fields can also be interesting. You will work in an interdisciplinary and international research
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student in Statistics who can perform high quality statistical research. Apply January 6, 2026, at the latest. We are seeking a PhD student within the WASP-HS project “Machine learning to study causality
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doctoral degree (PhD. in Computer Science). Start date: Spring 2026. Project Description This PhD project explores the foundations of tractable probabilistic models, i.e. machine learning models that support
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HCI and cybersecurity, to cancer research tools and methods for numerical analysis and machine learning. The research work takes place in a multidisciplinary team with a focus on image processing with
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series data. Large data sets come with significant computational challenges. Tremendous algorithmic progress has been made in machine learning and related areas, but application to dynamic systems is
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position within a Research Infrastructure? No Offer Description Project description Third-cycle subject: Human-Computer Interaction We are looking for a motivated PhD student to join a research project that
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, and the mathematical and computational foundations of neural networks. Familiarity with the following areas is meritorious: machine learning, computational complexity, tree automata and tree
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. The main research problems include mathematical theory, algorithms, and machine learning (deep learning) for inverse problems in artificial intelligence, as well as application to medical problems. About the
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an interest in Bayesian statistics, applied probability theory, computational mathematics, machine learning, and generative AI, and offers the opportunity to contribute to a rapidly growing research field with
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methods to rigorously assess the safety and effectiveness of medications in real-world patient populations. Defining individualized treatment strategies: Leveraging traditional and causal machine learning