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- NTNU - Norwegian University of Science and Technology
- NTNU Norwegian University of Science and Technology
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seasonal emissions such as winter CH4 emissions, using AI tools to develop upscaling tools or upscale to circumpolar region, or using climate modeling such as the Norwegian Earth System Model to constrain
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of smart technologies to visualize yard operations in a digital form (such as virtual models and digital twins). Smart technologies can collect, analyze, and represent data from various sources
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for simulating flow and pressure response, as well as thermal storage. Also analyzing new and existing data and calibrating models. Duties of the position Complete the doctoral education until obtaining a
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management using (and adapting) petroleum/CO2 storage tools for simulating flow and pressure response, as well as thermal storage. Also analyzing new and existing data and calibrating models. Duties
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models to resolve blade loads and structural responses under both operational and extreme conditions, including scenarios with partial out-of-water exposure Uncertainty quantification to ensure robust and
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access. The goals of such access include supporting registry operations as well as health care research. Of particular interest in this context are differentially private algorithms for statistical model
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approach of data-driven membrane discovery that includes material space construction and exploration, candidate selection and verification, providing data for machine learning models to optimise membrane
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numerical simulations from spectral wave and ocean models to produce high-resolution historical and future climate data. We encourage candidates with domain knowledge of wave modelling to apply, as
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qualities required for such purposes. Digital terrain models will be used to efficiently map cultural remains under forest canopies. The second project (Mapping Natural Forests in Norway) focuses on mapping
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are differentially private algorithms for statistical model parameter estimation under different trust relations. About the project The position is funded by the Norwegian Research Center for AI Innovation and will be