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educational programs, we are now seeking a postdoctoral researcher to work on privacy for data-driven models and high-dimensional data. The position is full-time for two years, starting on 1st September, or as
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The Department of Mathematics and Mathematical Statistics, Umeå University, invites applications for a two-year postdoctoral fellowship in data-driven analysis of a subarctic ecosystem near Kiruna
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are looking for candidates with a PhD in Computer Science, Visualization and Media Technology, Machine Learning or a closely related research field. A strong background in machine learning and visual data
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electronic structure calculations, in particular DFT, as well as basic knowledge of group-theory, are essential. Familiarity with data mining and/ or high-throughput DFT calculations is desirable but not
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collaboration with humans, adapting to their environment through sensors, information and knowledge, and forming intelligent systems-of-systems. The vision of WASP is excellent research and competence in
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forests and marine environment and pest surveillance in aquafarming. Our group will comprise a handful of PhD candidates, and several researchers and MSc students and also a broad interdisciplinary network
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arsenic, but other metals such as iron, manganese, lead and cobalt are also being investigated. At the department, you would take part in a strong and active scientific environment with other PhD students
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associated with different types of youth delinquency. The project uses data from the SOFIA study, a longitudinal prospective study that has followed about 2,000 children in a medium-sized Swedish municipality
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if there are special grounds, for example, different types of statutory leave of absence. Applicants who are close to finishing a PhD are also encouraged to apply. Further information The position is fully funded by
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of mathematical areas. The position will be placed at the Department of Computer Vision and Machine Learning (CVML) at the Mathematics Centre (https://maths.lu.se/). Mathematics Centre is a department