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landscapes using both proprietary and publicly available data sources Strong background in data analysis, preferably, proficiency with tools such as R. Experience with AI/ML-based approaches for data analysis
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wartime factors. Published and unpublished quantitative data, diaries, newspapers, government files, as well as files from municipal and regional archives will serve as source base. The PhD candidate is
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, government files, as well as files from municipal and regional archives will serve as source base. The PhD candidate is encouraged to develop their own approach to these questions, for example by focusing
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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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over time. For example, the contamination level may become critical, or on the contrary less urgent after a certain period. Two factors can be the source of such evolution, a physical one, where
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. As in freshwater sources, seawater in coastal areas is open to direct discharge from urban runoffs but also effluents of wastewater treatment plants, industries and ports, all of which may contain a
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ties, political beliefs, and gender roles, among other dimensions. Relying on individual-level information contained in parish and civil registers and population censuses (and other historical sources
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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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”, led by Associate Professor Valeria Vitelli. Successful candidates will work on Bayesian models for unsupervised learning when multiple data sources are available, mostly tailored to the case
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, including establishing and operating field measurements Experience with remotely sensed data and data sources Competence and experience in hydrological, glaciological or geophysical modelling Strong