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requirements To fulfil the general entry requirements, the applicant must have qualifications equivalent to a completed degree at advanced level (second-cycle), or completed course requirements of at least 240
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to two PhD students in Statistics for the research project “Next-Generation Latent Variable Models for Social Data Science”. Application deadline: November 4, 2026. We are seeking one to two PhD students
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PhD position in Experimental Physics with focus on photonics and materials science (applied aspects)
degree or completed course requirements of at least 240 ECTS credits. The recruitment procedure will follow the Higher Education Ordinance (Högskoleförordningen). Applicants should have a Master’s degree
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. The program addresses research on artificial intelligence and autonomous systems acting in collaboration with humans, adapting to their environment through sensors, information and knowledge, and forming
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and Microbial Ecology.” The project integrates human genetics, molecular biology, microbiology and microbiome analysis to investigate how host genetic factors shape the oral microbial ecosystem
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-cycle level degree, or completed course requirements of at least 240 ECTS credits, of which at least 60 ECTS credits are at second-cycle level or have an equivalent education from abroad, or equivalent
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adjustments to ensure that anybody can participate fully in the selection process. If you need an adjustment when accessing the application form, attending interviews, or for any other part of the application
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fuel cycle, from fuel reprocessing to final disposal, interfaces between water and metal oxides arise at which ionizing radiation induces radiolysis of the water. The species formed, free radicals and
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radiolysis of the water. The species formed, free radicals and other reactive molecules, can affect corrosion rates, the release of radionuclides, and the material properties of both reactor materials and the
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September 15, 2026 or as agreed. The application deadline is August 15, 2026. Project description The project aims to generate new knowledge on how households interact with energy systems in a sustainable