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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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the exploration of the evolving patterns of mountain ecosystems in response to climate and land-use change, and how these changes affect traditional cultural landscapes and ecosystem service provisioning 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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observational campaign on Folgefonna, a coastal ice cap in Western Norway, to establish an Earth System Model snow intercomparison dataset. This dataset will be complemented by in situ and UAV datasets
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land-use change, and how these changes affect traditional cultural landscapes and ecosystem service provisioning in the region. The successful candidate will join a multidisciplinary supervisory team
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management expert and a research assistant. AI STORIES explores the hypothesis that deep narrative structures in the datasets used to train generative AI models are replicated and perhaps exaggerated in
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of the art in mathematical and numerical modelling of CO2 storage? This might be the right position for you! About the project/work tasks: About the project TIME4CO2 TIME4CO2 aims at advancing simulation
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advanced systems for particle identification at low and intermediate momentum. This particularly involves the study of rare signals, including particles containing heavy quarks ("heavy flavours
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) period—primarily driven by natural climate variability—with contemporary retreat patterns influenced by anthropogenic climate change. The research will combine advanced remote sensing techniques with ultra