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consumption while guaranteeing optimal power production. You will work on the cutting edge of both wind energy and machine learning, two of the fastest growing scientific disciplines, to develop graph-based
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, these models often use simplified, linearized assumptions, limiting their capacity to capture the nonlinear complexities inherent in real-world hydrological processes. Recently, there has also been the branch
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scales and different phases which leads to nonlinear time and history dependent material behavior. Additionally, innovative changes are happening in the steel production process, especially in the drive
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scales and different phases which leads to nonlinear time and history dependent material behavior. Additionally, innovative changes are happening in the steel production process, especially in the drive