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simulation, composites manufacturing and advanced sensing techniques. The project will provide opportunities to develop skills in these areas and contribute to the development of the next generation composite
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scientists and software engineers. The team focuses on the following LISA deliverables agreed upon with the Norwegian Space Agency and ESA: Deliverable 1: Deployment and development of Norway’s computational
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power electronics to enhance the reuse and recycling of components, enabling a more circular life cycle. The work will contribute to a new paradigm in the development of power electronics that incorporate
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undertaking study in: Accounting and Finance Anthropology, Media and Performance Arab World Studies Architecture Business and Management Chinese Studies Criminology Development Policy and Management Digital
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and value creation in industry by developing better methods and smarter tools to do more with less—and faster. SFI-CELECT runs from 2026 to 2033 and is Norway’s most ambitious long-term research
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the noise associated with near-term quantum devices. This in turn offers an exciting new dataset from which it will be possible to use machine learning to train a more accurate functional for use in density
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integrates design, technology and management expertise. We link fundamental materials research with manufacturing to develop novel technologies and improve the science base of manufacturing research
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understanding how men could fare better in the modern world. Within the project, the successful candidate will be able to develop a research agenda focusing on health effects of men’s participation in the family
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they operate their aircraft. This project aims to develop metallic coatings for corrosion protection of components used at high temperature; similar environment as in aero-engine. The project will involves close
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nanosatellite/CubeSat constellations and to develop innovative GNSS-based sensing methods and AI models to detect a variety of Earth surface processes. This PhD position focuses on developing analytical models