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function Apply machine learning methods to identify optimal model parameters that can be used in large-scale sea ice simulations (either global parameters, or as a function of existing model variables like
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so development of new supply chains from green-field or adaptation of existing ones. Methodologies like simulation and life-cycle analysis, AI and data-driven design, will support the modelling and the development
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-manufacturing, re-use and use of by-products, development of new business models and so development of new supply chains from green-field or adaptation of existing ones. Methodologies like simulation and life
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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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balance simulations that support estimates of snow distribution for biodiversity and ecosystem assessments, as well as hydrological modelling and management plans for ski resorts and hydropower companies
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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 techniques
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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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. The candidate will apply (glacier-)hydrological models to simulate glacier-/snow- mass balance, runoff and extreme events from the past centuries (~1500) to the end of this century, using bias-corrected and
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flood events. The candidate will apply (glacier-)hydrological models to simulate glacier-/snow- mass balance, runoff and extreme events from the past centuries (~1500) to the end of this century, using
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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