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and accelerate the development of more high-performing PNSEs. The ultimate goal of the project is to develop, implement, and validate novel deep-learning models for molecular dynamics and coarse-grained
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this position, you will: analyze seaice properties and processes based on satellite data, remote sensing products, atmospheric and ocean data from numerical models, and in situ sea ice measurements
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regulates inflammation, cell death and infection outcome by using and further developing a human stem-cell-based model system recently established in the group. We are looking for a highly motivated PhD
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of interdisciplinary initiatives across the university. Department of Computer Science has an available 100% temporary position as Phd fellow in mathematical modelling. Your main duties and areas of responsibility
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, building ingredients, wettability, etc., and their interactions with water and gas species include CO2, Hydrogen and methane. Using atomistic modeling, the study will devote to design new hybrid porous
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materials, including porous dimension, building ingredients, wettability, etc., and their interactions with water and gas species include CO2, Hydrogen and methane. Using atomistic modeling, the study will
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that may threaten the emergence and long-term survival of habitable conditions on orbiting planets. This project places the modelling of cool star high-energy environments at its core, developing a
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on characterising and maturing Lower and Middle Triassic storage complexes in the Norwegian–Danish to North German basins, developing reservoir–seal models to identify new CCS acreage and helping to resolve potential
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, and deployability of deep learning models on resource-constrained edge platforms. The PhD candidate will collaborate closely with international project partners and contribute to advancing next
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environment. GIANTS is a five-year theoretical and numerical modelling project focused on the late stage of terrestrial planet formation involving giant impacts around the Sun and other stars. The project