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-of-computing-science/ Project description and working tasks The project will develop privacy-aware machine learning (ML) models. We are interested in data-driven models for complex data, including high
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mathematics, ecology, history, climatic and medical sciences in collaboration across multiple institutes. An integral part of the project is to develop process-based eco-epidemiological models considering
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biogeochemical responses. However, modeling these dynamics globally remains computationally challenging. To address this, our research employs advanced computational methods to simplify high-fidelity 1-D
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