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was ranked the 2nd best worldwide in Civil Engineering in the U.S. News Best Global Universities Rankings 2025, the 17th in Civil and Structural Engineering and the 27th in Environmental Science in
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for Artificial Intelligence. The position aims to strengthen methodological and algorithmic work on one or more of the following axes: Optimization and learning on very large models and datasets, improving
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the following is desired: - Agentic and sequential decision-making for autonomous experimentation, including active learning and optimal experimental design - Generative and probabilistic modeling
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/CZTSSe tandem solar cells and to establish advanced characterization under realistic operating conditions. The project will be structured around three main axes: 1) Development of tandem-compatible sub
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rôle fondamental dans la structure et le fonctionnement des environnements côtiers actuellement menacés par les changements globaux (CG). Parmi ces derniers, l'acidification (AO, acidification des océans
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Fraunhofer IGD and the FBN team to safeguard an efficient collaboration and communication between behavioural biologists and computer scientists. The project is part of the KI-Tierwohl project (https://ki
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that seeks to link material structure, transformation processes, performance properties (mechanical, thermal, fire resistance, absorption, etc.), and their evolution throughout the product lifecycle
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with 1000× increase in time resolution and 10× improvement in spatial resolution over prototypes. Such an instrument enables to measure the structure of heterogeneous systems including ageing concrete
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missions of the Primary Care and Population Health departments. This position will design and create data structures, reports, dashboards, and related data extracts from CUIMC?s Epic electronic health record
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—these approaches can recover unmeasured near-wall structures, improve subgrid-scale modelling, and enhance predictive accuracy. Possible project directions include: 1. Reconstructing near-wall velocity fields from