30 evolution "https:" "https:" "https:" "https:" "https:" "https:" research jobs at Chalmers University of Technology
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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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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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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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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
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tremendous potential to realize this vision. However, its large-scale implementation requires the development of new, scalable, precious-metal-free electrode materials. We are seeking a highly motivated
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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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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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bacteriology, we work with applications of various nanomaterials in biomedicine and biotechnology, metabolic engineering of microbial cell factories and experimental evolution. Our work is focused on societal
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(metabolomics, proteomics, microbiome, etc.) development of predictive models and digital decision-support tools for nutrition and health method development in causal inference, integration of heterogeneous data