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program som kan inneholde skadelige programmer eller virus. Hvordan nettsiden bruker cookies Cookies er nødvendig for å få nettsiden til å fungere. Cookies hjelper oss å få en oversikt over besøkene dine på
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din. En cookie er ikke et program som kan inneholde skadelige programmer eller virus. Hvordan nettsiden bruker cookies Cookies er nødvendig for å få nettsiden til å fungere. Cookies hjelper oss å få en
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of this Norwegian Cancer Society project. Both standard and advanced methods in molecular biology and cell biology are needed to carry out this project. Thus, the researcher is expected to act as self-driven
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at the intersection of cyber security, cyber-physical systems, and mathematical methods as part of the NORCICS Norwegian Centre for Cyber Security in Critical Sectors. The centre links researchers from
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program som kan inneholde skadelige programmer eller virus. Hvordan nettsiden bruker cookies Cookies er nødvendig for å få nettsiden til å fungere. Cookies hjelper oss å få en oversikt over besøkene dine på
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PhD Research Fellow in Experimental Fluid Mechanics: Tunable hairy surfaces for droplet flow control
Cookie-erklæringen var sist oppdatert 06.06.2025 Hva er en cookie? En cookie er en liten datafil som lagres på datamaskinen, nettbrettet eller mobiltelefonen din. En cookie er ikke et program som kan
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, methods and applications. The areas represented include: fluid mechanics, biomechanics, statistics and data science, computational mathematics, combinatorics, partial differential equations, stochastics and
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to the research group Harvest at the Norwegian College of Fishery Science (NCFS). The position is for a period of four years. The nominal length of the PhD programme is three years. The fourth year is distributed
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bringing together expertise and methods from different Climate Science, Ocean Biogeochemistry, Biological Oceanography, and Marine Ecology as well as the Ocean Modelling community, Social Science, Software
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The idea is to combine established iterative ensemble Kalman methods with novel emerging machine-learning-enabled model calibration techniques recently adopted in CLM-FATES at UiO. The aim is: to constrain