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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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the EU’s ambitious AI Factories initiative. Learn more: https://mimer-ai.eu/about-mimer/ , https://www.naiss.se , https://eurohpc-ju.europa.eu/ai-factories_en The position In this role your responsibility is
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out. N.B. When applying for the position we want you to provide a personal letter (first field in the application form). This letter should contain a paragraph where you briefly explain/list
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understanding of ionic and molecular transport at the implant-tissue interface and in the microenvironment around the implant. This will enable us to predict how these transport properties shape electrode
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themes that concern media, digital technology, internet infrastructure, heritage, algorithmic culture, materiality, or legacies of past social, political, or economic formations that continue to shape
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distributed wireless systems" which is conducted in collaboration between Linköping University (LiU) and Lund University (LU). Read more here: https://elliit.se/project/machine-learning-for-sensing-in
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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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visualization. Do you want to help shape the future of education? Your work assignments The advertised position is part of a Marcus and Amalia Wallenberg (MAW) foundation funded project that investigates