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., statistical methods for forensics, life sciences, topological data analysis, spatial statistics, and computational statistics). Learn more about the Department of Mathematical Sciences here . The Department
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associated with interpretation of measurements from blood and, in particular, measurements from a blood gas analyser. Often, blood samples can be incorrectly assessed due to gas contamination, delayed analysis
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deep learning, computer vision, medical image analysis or unsupervised learning is an advantage. English language skills, both written and spoken Qualification requirements PhD stipends are allocated
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-driven modelling. Experience with numerical modelling, simulation, optimization, control, or engineering-data analysis. Good programming skills in Python, MATLAB/Simulink, or a comparable scientific
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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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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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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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analysis. You master programming in for example Python, MATLAB, or a similar platform and you are motivated to further develop your skills in scientific computing and hyperspectral data processing. You have
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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