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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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, 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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description and working tasks The project will develop privacy-aware machine learning (ML) models. We focus on data-driven models for complex and temporal data, including those built from synthetic sources
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conversational guides for enhancing visitors’ learning and experiences in public educational environments. The PhD student will focus on addressing the challenge of visual blindness in large language models (LLMs
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development and application of novel data-driven methods relying on machine learning, artificial intelligence, or other computational techniques. Tasks The position is aimed at researchers early in their career
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research in the areas of condensed matter physics, nanotechnology, photonics, and theoretical and computational physics. We announce a PhD position for a project focusing on simulation and artificial
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research at the department, such as: real-time and embedded systems distributed systems security and privacy formal methods artificial intelligence and machine learning Pedagogical expertise The pedagogical
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are seeking a PhD student within the WASP-HS project “Machine learning to study causality with big datasets: towards methods yielding valid statistical conclusions” led by Professor Xavier de Luna and Tetiana