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modeling and model–data fusion techniques, and developing faster, machine-learning–based tools that can stand in for slow model simulations. These tools will be used to test how model parameters influence
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, computer science, physics, material science, earth science, life science, engineering, or a related field Proficiency in at least one programming language (Python, R, C++, Julia, …) Good analytical skills with a
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models, which are essential for understanding climate change impacts. The work involves reviewing existing modeling and model–data fusion techniques, and developing faster, machine-learning–based tools
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