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implement a framework to infer anisotropic viscosity from both ice and mantle textures in a numerical flow model. This will open new avenues for understanding solid earth and cryosphere dynamics, and their
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consisting of both control theory (or related fields) and economics (or related fields). Applicants must have experience in one or more of the topics: Model-predictive control Numerical optimization
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estimated stepwise from time series of the RS images, numerical models can provide continuous predictions of drift and deformation fields. This project shall investigate how the combined use of image time
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between ice and mantle dynamics. In DYNAMICE, we will implement a framework to infer anisotropic viscosity from both ice and mantle textures in a numerical flow model. This will open new avenues
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. They typically contain a combination of numerical, categorical, and textual data, and are often multilingual. DPPs are still evolving, facing challenges in data processing, handling missing or redundant data, and