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analysis Theoretical analysis of neural networks and deep learning Foundations of reinforcement learning and bandit algorithms Mathematical and algorithmic perspectives on large language models Statistical
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frontiers in the physical and mathematical sciences to lead the world in inquiry and impact. The purpose of MS-ADS is to advance the careers of diverse students for technical- and/or management-focused
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science, computational mathematics, combinatorics, partial differential equations, stochastics and risk, algebra, geometry, topology, operator algebras, complex analysis and logic. We have almost 50 persons
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projects, including several prestigious European Research Council (ERC) grants. In mathematics, the most popular research areas include probability theory, analysis and partial differential equations
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We address a broad range of fundamental and applied evolutionary problems via the identification and analysis of genetic and phenotypic variability underlying biodiversity at all taxonomic levels
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, and/or multiphysics modelling • Mathematics & AI: Numerical analysis, inverse problems, neural networks, scientific machine learning • Programming: Python (scientific computing, ML), preferably C
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to capture the spatial complexity of tumor organization and its relationship to treatment response. This PhD project aims to develop robust multimodal predictive models of platinum resistance using a large
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science solutions in a business or research context, and experience of data transformation, data analysis and statistics. Ability to communicate complex technical information to non-experts and engage with
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for specialization in actuarial science, pure and applied mathematics, and data-driven quantitative fields. The department’s faculty pursue fundamental and interdisciplinary research in algebra, analysis
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successfully developing methods to integrate large and complex preference datasets with information at individual level, with specific attention to open and reproducible research, e.g., in the development