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within the project, including data collection, analysis, scientific reporting, and dissemination. Supervision of students may be included. The postdoc will primarily work with: • Co-creation and
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into real impact. At the division of Data Science and AI , we develop data-driven methods and AI solutions that support intelligent decisions across society, advancing machine learning techniques, from
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sustainable energy technologies. About us The Division of Chemical Physics conducts internationally recognized research at the interface of physics, chemistry, materials science, and data science. Our research
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interpreting SANS/SAXS data both within the project and other projects in the research group. Teaching in the first, second or third cycles of studies Supervision of degree projects and doctoral students
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stability, reduced leakage risks, and improved energy density. This project focuses on developing efficient materials and synthesis methods that can improve ionic conductivity, battery safety, cycle life, and
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. For more information about the Akelius Math Learning Lab, see: https://www.chalmers.se/institutioner/mv/akelius-math-learning-lab/ Who we are looking for The following requirements are mandatory: Doctoral
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interests encompassing research on metal/semiconductors, nano-materials, organic molecular and silicon-based solar cells, (see https://www.kau.se/en/physics/research/materials-physics ). The research
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mechanical modelling, such as finite element analysis (FEA). experience of working with healthcare professionals and patients. strong knowledge of statistical methods, including non-parametric methods
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motto today as it did then: Avancez – forward. URL to this page https://www.chalmers.se/en/about-chalmers/work-with-us/vacancies/?rmpage=job&rmjob=14631&rmlang=UK
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expression and purification and/or optogenetics, particularly as applied to the control of cell wall synthesis or remodelling enzymes. Experience with confocal microscopy and quantitative image analysis in