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department is available at: https://www.umu.se/en/department-of-computing-science/ Project description Graph transformation is a well-established theory that studies computational methods to transform graphs
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algorithms and methods for calibrated Bayesian federated learning for trustworthy collaborative Bayesian learning on data from multiple participants. The project will develop new methods, theory, and
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education to enable regions to expand quickly and sustainably. In fact, the future is made here. The Department of Physics at Umeå University (https://www.umu.se/en/department-of-physics/ ) conducts strong
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tools, which can be used to analyze massive amounts of scMetaG data. In addition to being affiliated with the Department of Clinical Microbiology at Umeå University (https://www.umu.se/en/department
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that yield valid statistical conclusions (inference) on causal effects when using machine learning algorithms and big datasets. The project is part of the research environment Stat4Reg (www.stat4reg.se ), and
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opinion dynamics, starting January 2026 or by agreement. Research project This PhD project will be carried out as part of the WASP-HS Research Cluster AI, Power and Politics (https://www.umu.se/en/research
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part of a research group active in the area of molecular geochemistry (http://moleculargeo.chem.umu.se ) at the Department of Chemistry (https://www.umu.se/chemistry ), with many years of experience in
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employment conditions. More information about the department is available at: https://www.umu.se/en/department-of-computing-science/ This is a joint PhD position with the Umeå Centre for Gender Studies
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Tomon. More information about Discrete Mathematics at Umeå University can be found on the group’s homepage: https://www.umu.se/en/research/groups/discrete-mathematics/ As a PhD student, you will be part
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an employee at Umeå University here: https://www.umu.se/en/work-with-us/benefits/ . Application You apply via our e-recruitment system Varbi. Log in and apply via the button at the bottom of the page