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methods (e.g. chamber-based gas flux measurements, soil sampling etc) Place of work: Umeå Forms for funding or employment: Employment as PhD student, full time for 4 years Starting date: During spring 2026
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design with advanced structural, spectroscopic, and electrochemical characterization methods to unravel how ions, charges, and molecular interactions govern doping efficiency and stability. By exploring
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theory and probabilistic methods, and it hopes to clarify how these two settings, hypergraphs and posets, connect through their shared saturation questions. Combinatorics and mathematics in Umeå
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independently using the right methods, and to develop an awareness of research ethics. In addition, you will have the opportunity to work on projects, to develop your leadership and pedagogical skills. Throughout
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funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Are you interested in working with machine learning methods with the support of
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PhD position within the Infection Medicine Research Group The research group is led by Johan Malmström, whose goal is to develop methods within proteomics to promote the implementation of precision
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and methods for energy systems integration of the AI agent with energy system models methods for transparency, explainability, and uncertainty handling applications in case studies related
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with experimental methods in spectroscopy or diffraction, as well as familiarity with basic programming. Consideration will also be given to the applicant’s ability to collaborate, their motivation and
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the 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
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thoroughness, logical reasoning skills, and strong problem-solving abilities. Merits are: practical experience with experimental methods in spectroscopy or diffraction, as well as familiarity with basic