312 evolution "https:" "https:" "https:" "https:" "Keele University" research jobs in Sweden
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, in close collaboration with wider society. 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
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research within Unmanned Traffic Management (UTM). In this role, your primary responsibility will be the hands-on development of advanced simulations and prototypes that help us test and validate new UTM
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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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European Universities in several EU aviation projects About the research project EXAELIA The project is related to the development of future aircraft concepts and propulsion technology that has
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on the long term globally distributed WaRM experiment (for details see here: https://onlinelibrary.wiley.com/doi/10.1002/ece3.9396 ). The employment is fulltime for three years. The deadline
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Website https://umustipendie.varbi.com/en/what:job/jobID:887298/type:job/where:39/apply… Requirements Research FieldMedical sciencesEducation LevelPhD or equivalent Research FieldMedical sciencesYears
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within the department, and how they stand to contribute to its future development. Further requirements: Strong knowledge and hands-on experience in aqueous battery technologies, particularly iron- and/or
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- for technical and societal development. Our cross-disciplinary approach gives interesting collaborations in academy, industry and society, and is a driving force for innovations, results and breakthroughs. We
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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