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application! We are seeking a highly motivated PhD student to join a research project at the forefront of battery diagnostics and modelling, that will help shape the future of battery technology by developing
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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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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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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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not be considered. In the application please provide a personal letter (first field in the application form). This letter should contain a paragraph where you briefly explain/list the qualifications
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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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-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