173 data-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"https:" positions in Denmark
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part of the application. Contact information For further information, please contact Associate Professor Andreas Pavlogiannis at [email protected] Application procedure Shortlisting is used
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employment The place of work is Universitetsbyen 81, 8000 Aarhus C, Denmark, and the area of employment is Aarhus University with related departments. Contact information For further information, please
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methods for approaches such as model-data fusion techniques. The main focus of your position will be to develop and apply a scalable process-based modeling framework to evaluate climate-smart management
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Machine and Deep Learning – Applications and Case Studies in Business AI Agents and Agentic Workflows in Business Explainable AI (XAI) E-commerce, Web and Social Media Analytics Big data analytics Natural
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statistics have been a key element in your work. Experience with data handling and flexibility in using a wide range of statistical methodologies, both frequentist and Bayesian. Demonstrated proficiency in
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with relocation and career counselling to expat partners. Please find more information about the International Staff Office and the range of services here . Aarhus University also has a Junior Researcher
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conduct local Danish data collection and perform collaborative and comparative analyses of the data. The following tasks will all be core activities: Conduct and analyse focus group interviews with Danish
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information can be found here. We believe in encouraging inclusion, acceptance, and understanding by employing staff who bring unique perspectives to our department. What we offer A collaborative, international
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as part of the ORBIT Consortium. Work duties (e.g., data collection) will take place mainly in Denmark, but may also include data collection and participation in meetings in Sweden, Norway, and Finland
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PhD Scholarship in Development of Cement-Free Living Building Materials for Sustainable Construction
construction applications Generating, processing, and critically analyzing experimental data using advanced characterization techniques Publishing high-quality research in leading international journals and