149 data-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "Univ" "UNIV" "UNIV" "UNIV" positions at Chalmers University of Technology
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28 Feb 2026 Job Information Organisation/Company Chalmers University of Technology Research Field Computer science » Other Engineering » Control engineering Engineering » Electrical engineering
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28 Feb 2026 Job Information Organisation/Company Chalmers University of Technology Research Field Computer science » Other Engineering » Control engineering Engineering » Systems engineering
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it effect engagement and learning. For more information about the Akelius Math Learning Lab, see: https://www.chalmers.se/institutioner/mv/akelius-math-learning-lab/ Who we are looking
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Research FieldPhysicsYears of Research Experience4 - 10 Research FieldTechnologyYears of Research Experience4 - 10 Additional Information Website for additional job details https://academicpositions.com Work
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FieldEngineeringYears of Research Experience4 - 10 Research FieldTechnologyYears of Research Experience4 - 10 Additional Information Website for additional job details https://academicpositions.com Work Location(s
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analytical and mathematical skills, including proficiency in quantitative modeling, data analysis, and scientific computing (e.g., R, Python). Strong written and verbal communication skills in English. *for
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experiments. Information about the department The Department of Microtechnology and Nanoscience advances the frontiers in quantum technology, nanoscience, photonics and future electronic systems
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Research FieldLanguage sciencesYears of Research Experience1 - 4 Research FieldPsychological sciencesYears of Research Experience1 - 4 Additional Information Website for additional job details https
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equality and inclusion as fundamental aspects of all our activities. If Swedish is not your native language, Chalmers offers Swedish courses to help you settle in. Find more general information about
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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