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floods—in mountain catchments. The goal is to understand long-term changes in runoff regimes and flood hazards by combining climate-driven (glacier-)hydrological modelling with reconstructions of past
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. The models can build on recent research results in foundational neural network models. The work will be done in collaboration with Kongsberg Satellite Services in Tromsø. The position is located in Oslo, but
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Planning, Marine Protected Area Planning and Systematic Conservation Planning. Experience with models and simulations of marine species distributions, oceanographic parameters, and/or human activity (e.g
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of agroecological farming in EuRope ), funded by the Research Council of Norway. About the project/work tasks: As a postdoc within a large international and interdisciplinary team you will use spatial modelling
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snow in local and regional climate models is poorly constrained, leading to uncertainties in estimating mass loss through sublimation and snow redistribution. The PhD candidate will develop and execute
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of blowing snow in driving accumulation and sublimation in mountainous conditions. The simulation of blowing snow in local and regional climate models is poorly constrained, leading to uncertainties in
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networks”, meeting and exchanging biomolecules in a cellular society. The reasons for this behaviour remain poorly understood, and outside of some model species, this behaviour itself is poorly characterised
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green transition. About the project/work tasks: The overall goal of this PhD project is to develop methodologies for real-time modeling and inversion of geophysical well logs, with a particular focus on
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, key Arctic geological archives of past warmth and employ climate models to bring our current knowledge about a warm Arctic beyond the state-of-the-art. The major strength and aim of i2B
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“greenhouse” (warmer than present) conditions. In i2B we will retrieve new, key Arctic geological archives of past warmth and employ climate models to bring our current knowledge about a warm Arctic beyond the