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following: Data Science, Machine Learning, Computational Social Science, Big Data. Relevant skills could include statistical analysis, data management and collection, causal inference, network analysis, graph
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include statistical analysis, data management and collection, causal inference, network analysis, graph theory, visualizations, and online tool development. Experience in conducting online controlled
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networks and deep learning Foundations of reinforcement learning and bandit algorithms Mathematical and algorithmic perspectives on large language models Statistical learning theory and complexity analysis
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research interests might be considered, priority will be given to those able to relate to one or more of the above topics. Applicants must have a PhD in Mathematics, Statistics or Computer Science obtained
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algorithmic perspectives on large language models Statistical learning theory and complexity analysis Automated theorem proving and formal methods Random matrix theory and its applications in modern AI systems
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language models Statistical learning theory and complexity analysis Automated theorem proving and formal methods Random matrix theory and its applications in modern AI systems This position can be filled
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Mathematics, Statistics or Computer Science obtained within the last 5 years. Applications are open immediately and will be reviewed on a rolling basis until the position is filled. The position becomes vacant
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perspectives on large language models Statistical learning theory and complexity analysis Automated theorem proving and formal methods Random matrix theory and its applications in modern AI systems This position
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, statistical signal processing, optimization theory, machine learning and artificial intelligence. The candidate is expected to actively participate in experimental work focused on building datasets of channel