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exhibitions. About the PhD project and work tasks The successful candidate’s PhD project will investigate narrative through computational models, for instance, those based on processes of storytelling, creative
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technological progress in our increasingly digital, data- and algorithm-driven world. Integreat develops theories, methods, models, and algorithms that integrate general and domain-specific knowledge with data
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of three topics: 1. Combining synthetic aperture radar (SAR) images with probabilistic weather prediction models to view and predict dynamic sea ice properties. 2. Using multi-frequency SAR, coupled with in
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contemporary streaming data scenarios, such as evolving baselines and complex, data-intensive settings. The applicant must master theoretical work in the field of change and anomaly detection and estimation, as
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. Experimental work could include the design, construction, and testing of prototype storage systems, while simulation efforts may focus on thermal modelling, system optimization, and safety analysis
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. Integreat develops theories, methods, models, and algorithms that integrate general and domain-specific knowledge with data, laying the foundations of next generation machine learning. We do this by combining
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well as of the cyclone family itself. The candidate will investigate the mechanisms by which moisture is drawn into and processed within cyclone families using reanalyses, idealised and realistic model simulations
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updates, and interoperability at scale. In close collaboration with project partners, the PhD candidate will focus on relevant data modeling and processing approaches for data gap filling, redundancy
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Integreat develop theories, methods, models, and algorithms that integrate general and domain-specific knowledge with data. By combining the mathematical and computational cultures, and the methodologies
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at Integreat - Norwegian Centre for Knowledge-driven Machine Learning is a Centre of Excellence, funded by the Research Council of Norway. Researchers at Integreat develop theories, methods, models, and