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structured around two main pillars: Network resilience and sovereignty, i.e., research on networking architectures and mechanisms that keep critical networks and applications they support running optimally
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AI models into complex industrial and urban environments. Expertise in designing distributed architectures for IoT, edge, and cloud. Proficiency in handling large-scale data and optimizing information
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opportunities in combining physical meteorological/hydrological/hydraulic modelling and AI methods to improve the inflow prediction, and optimize the control of and use of water in the water courses considering
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. The position is part of a small team that works on the development and optimization of algorithms for these problems, as well as proofs on theoretical complexity bounds. Common tasks include: Developing ideas
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narrative teaching portfolio outlining prior teaching experience and pedagogic qualifications (max 3 pages; optimally organized around the four principles of Scholarship of Teaching and Learning in Higher
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in crystalline rocks. Drilling optimization using machine learning, e.g. predicting rate of penetration (ROP) and wear. Investigate the possibilities in automation and robotization and the use
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stresses, drill wear (bit replacement). Collect and analyze existing and new data on drillability related to mineral content and degree of metamorphosis in crystalline rocks. Drilling optimization using
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will have access to an optimal health service, as well as good pensions, generous maternity/paternity leave, and a competitive salary. Nursery places are guaranteed and reasonably priced relocation
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working capacity, and increasing the number of professionally active seniors "Hjem-jobb-hjem" discounted public transport to and from work as an employee in Norway, you will have access to an optimal
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storage in depleted petroleum fields: In this project, you will investigate and aim to optimize CO2-assisted oil production (CO2EOR) and subsequent CO2 storage. Simplistic models for a fundamental