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to strengthen the fundamental research potential of the J. A. Dieudonné Research unit at the Assistant Prof. (Maitre de conférences) level, with a profile primarily oriented towards classical analysis and its
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suitable data models [CSC+23]. Objectives As far as the design of efficient numerical algorithms in an off-the-grid setting is concerned, the problem is challenging, since the optimization is defined in
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. The Department of Computer Science (DCS), headed by Prof. Dr. Jean-Sébastien Coron ( jean- ), is opening an Assistant / Associate Professor (depending on qualifications) position in Theoretical Computer Science
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a breakthrough concept to upgrade existing fiber optic networks to acoustic sensor arrays, becoming a key component for managing smart cities. Except for a few applications, DAS data are typically
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algorithms for dynamic structured data, with a particular focus on time sequences of graphs, graph signals, and time sequences on groups and manifolds. Special emphasis will be placed on non-parametric
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complicates both learning and inference processes. Another challenge is that dynamic structured data are generated by a variety of sensors and infrastructures that continuously produce, disseminate, and store
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, sensor failures, or the aggregation of datasets from multiple sources. There is a rich literature on how to impute missing values, for example, considering the EM algorithm [Dempster et al., 1977], low
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detection, to cite a few. As telecom fibers are ubiquitous in urban environments, DAS appears as a breakthrough concept to upgrade existing fiber optic networks to acoustic sensor arrays, and a key component
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contact Prof. Ralf Seppelt, Your profile You'll be able to demonstrate experiences in management environmental data in different projects, and meet the following qualifications: PhD in Data Science
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through innovative solutions. Coordinated by Prof. Francesco Vitti from the Engineering department, NEXTLOGIC is funded under the HORIZON-MISS-2024-CIT-01 call: Changing urban spaces and mindsets