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criteria Competencies on IOT and Sensor technologies Competency and experience in AI methods Good communication skills - written and oral Good oral and written presentation skills in Norwegian/Scandinavian
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particular to the development and validation of novel computational language models, algorithms, and tools for spoken language-based cognitive tests for low-resource languages, and their integration with
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/Machine Learning (AI-ML) approaches to meeting this challenge. Possible topics include, but are not limited to: storylines for plausible narratives of regional climate change, novel algorithms for rare
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making, analyzing patterns across different livelihood systems, such as hunter-gatherers, animal herders and subsistence farmers in different parts of the world. This research addresses a critical gap in
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for plausible narratives of regional climate change, novel algorithms for rare event sampling or ensemble boosting, and the development and use of hybrid climate models combining physics-based and ML components
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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 domainspecific knowledge with data
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ethnography of meaning making, analyzing patterns across different livelihood systems, such as hunter-gatherers, animal herders and subsistence farmers in different parts of the world. This research addresses a
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, algorithms and systems architecture. Interest in functional programming and other programming paradigms is also relevant. ETL, data wrangling and data analytics Competence in mathematics/statistics
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power engineering. In condition monitoring non-invasive data is analyzed through machine learning algorithms or by statistical methods. The aim of predictive analysis is to use non-invasive methods
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centres on natural science disciplines, particularly meteorology, emerging sensor technology, citizen science, and the development of early warning systems for location-specific natural hazards