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-food crops, labour exploitation and the multi-faceted impacts of climate change. This research project will explore how the market can respond to these challenges of polycrisis by delivering research in
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algorithms suitable for multi-static and distributed geometries. Understanding the performance limits of such systems, including sensitivity to synchronisation errors, geometry, transmit time, and partial
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looking for a PhD candidate to join our research project entitled “Next-Generation Cognitive Testing: A Theory-Driven Approach to Multi-Scale Dynamics in Cognition”, funded by an ERC Consolidator grant
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Inria, the French national research institute for the digital sciences | Villers les Nancy, Lorraine | France | 5 days ago
massively distributed environment (cloud-edge continuum). The PhD will be located at The Inria Center of the University of Lorraine in the Loreley team. It will be supervised by Claudia-Lavinia Ignat
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Engineering) Laboratory, your goal is to design and build the core predictive engine for this platform, teaching microscopes how to think and helping develop the next generation of beamlines. This is a cutting
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maintaining national networks of geophysical instruments, and by operating a data center. The thesis will be conducted within the Waves and Structure Team, under the supervision of Nikolai Shapiro and Laurent
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at the Ecole polytechnique research centre working on the frontier of knowledge on the major interdisciplinary scientific, technological and societal issues. Within the Teaching and Research Department of Ecole
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known for its high-impact research, aimed at solving problems across the globe. Interdisciplinarity, experiential learning, and connection to partners beyond academia are at the heart of the Northeastern
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behaviours of multi-agent systems in response to changing internal states and external environmental conditions. Both traditional model-based approaches and modern learning-based control techniques will be
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modelling, data assimilation, and multi-scale neural network architectures applied to spatio-temporal data. The development of these methods is motivated by a concrete and important application: inferring gas