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announcing a PhD position in Logistics focusing on Immersive media technology environments in the analysis of consumer response in circular value chains. The PhD position is organized under Department
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Element simulations (e.g. pushover analysis and/or incremental dynamic analysis). Moreover, the project aims to verify the ductility requirements with full-scale experimental results and explore
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criteria Demonstrated knowledge and experience in electrical system modeling and analysis, applied control, power electronic systems, optimization techniques, and/or machine learning. Experience with
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challenges in machine learning for short multivariate time-series analysis. By developing a multiway and multitask learning framework with built-in explainability, the project aims to deliver clinically
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the possibility to specialize in one in consultation with the supervisors and the project leadership: • Policy Document Analysis: Utilizing document and content analysis, including text mining, to identify
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Demonstrated knowledge and experience in electrical system modeling and analysis, applied control, power electronic conversion systems and/or optimization techniques. Experience and interest in experimental work
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this emerging field in close cooperation with our research group and the industry. The goals of the PhD project include: Analysis of the sources of CO2 with potential for delivery to the CCS facilities in
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learning is required. Experience with spectral wave modeling is an advantage. Experience with ocean modeling is an advantage. Experience with metocean data analysis is an advantage. Experience with git
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computational skills (using R, modelling software, working on a remote linux-based server) and experience in analyzing Next Generation Sequencing data, including PCA, outlier analysis, GO-term enrichment analysis
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state-of-the-art skills in health statistics and data analysis. The study focuses on enhancing the interpretability and precision of NF scores by developing normative ranges and clinical thresholds