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, data analysis, and dissemination of research findings. The project combines perspectives from systemic innovation, integrated care, and health economics. The PhD student will collaborate closely with
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, or higher education) Experience with developing immersive technologies (e.g., XR/VR/AR) and/or doing multimodal data analysis (e.g., eye-tracking, gesture tracking, interaction analysis). You can Write
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Learning and data analysis and are motivated to apply these skills to complex materials and production systems. You are familiar with polymer materials and processing, and you have knowledge of techniques
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colleagues dealing with CCUS, and industrial partners in Denmark as well as abroad. Your primary tasks will be to: Perform physical-chemical analysis of solvents and gases Perform corrosion experiments
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data sources (e.g., registry data, surveys, and organisations). Your competencies Digital methods such as machine learning based classification, computational text analysis, network analysis, web
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research questions, and be able to think critically and develop your own scientific ideas. Previous experience with statistical analysis, programming (e.g., R or Python), machine learning, or genomic data
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Build, Division of Civil and Environmental Engineering, within the general study programme Civil Engineering and work with numerical modelling, time series analysis, and soil characterization
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should have hands-on experience with microfabrication, nanofabrication or experimental device work, and be comfortable with systematic laboratory work, data analysis and troubleshooting. The project spans
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onwards. Through a combination of history of emotions, educational history, historical ethnography, and policy analysis, the project explores how students' discomfort with, resistance to, and disengagement
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o calibration and/or data assimilation o satellite geodetic and/or Earth Observation (EO) data processing o meteorological/hydrological data processing and analysis Strong interest in collaborative