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-efficiency requirements at the energy edge. Further, you will incorporate compliance-by-design AI architectures and models and validate our solutions across key energy use cases such as energy market
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of future reactor systems with a focus on systems relevant for Norway. The objective is to further develop and validate machine-learning surrogate models derived from high-fidelity multiphysics simulations
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Bayesian inference, probabilistic modeling, and machine learning, the project aims to make Arctic observations more efficient, intelligent, and impactful. You will integrate field observations—including
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the ecosystem structures, governance mechanisms, business model innovation and organizational capabilities needed to develop and scale AI solutions for sustainable industry. The overarching research
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publication record in psycholinguistics, Nordic linguistics, corpus linguistics, sociolinguistics, or related fields Experience with R (data wrangling, visualization, statistical modelling) Experience with
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. The project The position is affiliated with the Aerospace Engineering activities at UiT in Narvik, which include research on autonomous spacecraft systems, CubeSat missions, formation flying, Model-Based
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compliance-by-design AI architectures and models and validate our solutions across key energy use cases such as energy market optimization (demand response, transactive energy peer-to-peer trading, and
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. Integreat develops theories, methods, models, and algorithms that combine data with general or domain-specific knowledge, helping lay the foundations for the next generation of machine learning. Integreat
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artificial intelligence (AI) and an increasingly important force in a digital and data-driven world. Integreat develops theories, methods, models, and algorithms that combine data with general or domain
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the Department of Geosciences. PHAB’s main goal, based on detailed studies of Earth and the solar system, is developing predictive models to identify habitable planets around other stars. Within three