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the research project This project is set to explore so-called shared control between the driver of a car and the car's safety systems. By mechanically disconnecting the driver's steering wheel from
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such as energy, industry, consumption, and urban development. At the research frontier, the application of AI and machine learning is enabling novel pathways for sustainability transitions. These include
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systems, and machine learning. While the initial focus of the position is on this project, we offer significant opportunity for the applicant to develop their own independent research trajectory in
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receive five weeks of training in teaching and learning in higher education and also get the opportunity to learn Swedish through the University’s Swedish language courses for new international staff. We
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of AI and machine learning methods for advanced modelling and analysis of energy and industrial processes Experience with high-temperature processes, particularly in metal and mineral processing
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, computational materials science, computer science, or a related field, awarded no more than three years prior to the application deadline*. Background in physics-based battery modelling and/or machine learning is
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machine learning techniques into a modern AI planning system. The project will involve both theoretical and experimental work As a PhD student, you devote most of your time to doctoral studies and the
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great advantage: Forest and wood production processes Wood construction Furniture manufacturing Wood material science Machine learning Process simulation and optimisation The postdoctoral fellow is part
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of MSI advances our understanding of complex brain processes. The prospective PhD candidate collects brain MSI data and develops novel machine learning methods in connection to generative models such as
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senior lecturer and eventually professor. You will receive five weeks of training in teaching and learning in higher education and also get the opportunity to learn Swedish through the University’s Swedish