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application! Work assignments AIR2 is a five-year multidisciplinary national project financed by the Wallenberg AI, Autonomous systems, and Software Program (WASP) whereby you will have the opportunity
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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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- 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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organizations. Facilitate co-creation workshops to help organizations identify and clarify AI use cases. Build and coordinate a network of trainers, experts and partner organizations. Collaborate with
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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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systems (e.g., UAVs or robots), or High-availability networking infrastructures (e.g. 5G and beyond) will be considered as a plus. In this multi-disciplinary national project we seek candidates with strong
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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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networks. Teaching is primarily directed at Master’s-level students in engineering programmes. Both teaching and research are largely campus-based and collaborative in nature, which means that most work is
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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