95 evolution "https:" "https:" "https:" "https:" positions at Chalmers University of Technology in Sweden
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collection in real-world settings as well as controlled user studies, alongside the development of new theoretical models of human-robot communication. The PhD candidate will be supervised by experts in
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, learning and outreach. The research topics at the department span from fundamental to applied research with the aim of contributing to the development of a sustainable society. A wide range of experimental
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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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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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the mechanical properties of conjugated polymers and on the development of spinning processes for the manufacture of conducting polymer fibers for wearable electronics. A summary of the research field can be found
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This project focuses on the development of quantum–classical modeling strategies for multiphase flow systems. The PhD topic is on exploring how emerging quantum computing methods can be integrated with classical
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technology, nanoscience, photonics and future electronic systems - for technical and societal development. Our cross-disciplinary approach gives interesting collaborations in academy, industry and society, and
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international academic institutions and 14 industry partners (https://euraxess.ec.europa.eu/jobs/401249 ). We work together in the field of fluid-structure interaction in technical systems and industrial
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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