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application! We are looking for a PhD student in automatic control at the Department of Electrical Engineering (ISY). Your work assignments The research area for the position is complex networks and multi-agent
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will build on research that detects different types of uncertainty in deep neural networks, and we will connect this uncertainty to interactive data collection, e.g. in the form of a dialogue with the
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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
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- 12:00 (UTC) Country Sweden Type of Contract To be defined Job Status Full-time Hours Per Week 40 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job
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are not limited to, numerical methods of high order, Discontinuous Galerkin methods, path conservative discretisations, efficient time integration, and energy / entropy stable methods. Curvilinear mesh
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research presentations. The exact research direction will be defined jointly with your supervisors. As a PhD student, you devote most of your time to doctoral studies and the research projects of which you
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through publications and research presentations. The exact research direction will be defined jointly with your supervisors. As a PhD student, you devote most of your time to doctoral studies and the
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-scale neural network models. While the developed methods will be broadly applicable, particular emphasis will be put on the problem of inferring gas dynamics in urban environments. Gas dynamics shape air
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developer Batixt and an international research partner at Sungkyunkwan University in South Korea. This provides a unique opportunity to validate methods on real systems and data from production, operation
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communications see our review paper entitled “Semantic Communications in Networked Systems: A Data Significance Perspective” published in IEEE Network, vol. 36, July/August 2022. The project is part of a