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- NTNU - Norwegian University of Science and Technology
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the period 2008 to 2024 will be used to analyse the use of health services, medicines and sickness absence. The source data include linked data from the primary and specialist health services
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novel computational models for intelligent analysis multi-variate time-series data during their PhD studies. actively take part in inter- and multi-disciplinary research activities relevant to AI Hub
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headquarters in Trondheim. At NTNU, 9,000 employees and 43,000 students work to create knowledge for a better world. You will find more information about working at NTNU and the application process here
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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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storage (CCS) value chain could play an important role in achieving these targets and support local industrial development. As a PhD candidate, you would be expected to contribute to the research within
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educational programs in health and social science professions, as well as continuing and further education, and several master's programs. The faculty offers the PhD program “Health, Function, and Participation
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cities with headquarters in Trondheim. At NTNU, 9,000 employees and 43,000 students work to create knowledge for a better world. You will find more information about working at NTNU and the application
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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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the project The position is part of the EU Horizon project EU-INTERCHANGE (European Regional and Coastal Seas in a Rapidly Changing Climate) aiming to develop a Digital Ocean Twin based on optimised
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Dissertation on a topic in business economics, industrial organisation, public finance, asset management, risk analysis, shipping economics, or the economics of natural resources Core courses in probability and