42 evolution "https:" "https:" "https:" "https:" "https:" "https:" "Universitat de Vic (UVIC UCC)" research jobs at Chalmers University of Technology
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Join us at the Division of Astronomy and Plasma Physics, Department of Space, Earth and Environment, and help advance our understanding of galaxy evolution and supermassive black hole growth. Do you
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degree, obtained within the last three years prior to the application deadline Experience of teaching at undergraduate or master’s level, and an interest in further development within teaching and
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, etc.) development of predictive models and digital decision-support tools for nutrition and health method development in causal inference, integration of heterogeneous data sources, uncertainty
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and Plasma Physics (AoP), we investigate the origins and evolution of the Universe – from star and planet formation to galaxy dynamics and the physics of fusion plasmas. Through international
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to the application deadline What you will do In this poisition, you will be central to the development of the project, and also responsible for the implementation, validation and data analysis of the numerical tools
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. Chalmers was founded in 1829 and has the same motto today as it did then: Avancez – forward. Where to apply Website https://academicpositions.com/ad/chalmers-university-of-technology/2026/postdoc
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quantum technology, nanoscience, photonics and future electronic systems - for technical and societal development. Our cross-disciplinary approach gives interesting collaborations in academy, industry and
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Transfer Operators [4 ,5 ]. The Postdoc will lead both the conceptual development in close collaboration with the project’s Principal Investigator, and practical implementation of this research with
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collaboration meet. The research topics in the department span fundamental and applied research to contribute to the development of a sustainable society. We are Sweden's largest mathematical department, with
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targets the development of advanced grey-box modeling frameworks for multiphase flow systems, combining mechanistic, multi-scale flow models with data-driven inference and uncertainty quantification