104 evolution-"https:" "https:" "https:" positions at Chalmers University of Technology
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team of doctoral students, postdocs and researchers. The staff scientist position is a research support role, focused on assisting research activities through method and/or instrument development. Job
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future electronic systems - for technical and societal development. Our cross-disciplinary approach gives interesting collaborations in academy, industry and society, and is a driving force for innovations
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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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durability of engine materials. The project is expected to generate new knowledge and expertise that will contribute to the development of sustainable vehicle propulsion systems. An additional important
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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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system developer for our national DDLS data services, with a profile towards data engineering, systems development, and data management. In this role, you are expected to develop software, systems, 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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that prevail at very small dimensions, and promote the development of technologies that utilise these phenomena. About the research project The topic of the PhD project will be about tunable self-assembled
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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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This project 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