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. The project involves the development and modelling of hydraulic systems, with particular emphasis on energy-efficient system architectures and appropriate component selection. A key aspect is to incorporate
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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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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
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engineering, and the built environment. Research at BUILD is rooted in engineering science and integrates important elements from environmental science, social sciences, and the humanities. AAU BUILD is a
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potential. Detecting and diagnosing these faults early at the component, building, and city-district level is essential for the sustainable cities of tomorrow. This PhD project addresses a fundamental
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At the Faculty of Medicine, Department of Clinical Medicine, Aalborg University, a PhD stipend in genetic analysis and cardiovascular disease is available for appointment from October 1, 2026
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quantitative analysis of data from experiments and other sources. This may include studying how blind screening and structured interviews affect the representation of different groups in selection processes