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efforts to contribute to safer marine operations, we actively explore possibilities to utilize both numerical and machine learning methods to enhance the accuracy and resolution of metocean forecasts. About
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the PhD candidate may include (non-)linear inverse load estimation and data-driven/machine learning techniques that rely on physics-informed guidance for improved robustness. A key task will be to quantify
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relevant experience in the development and deployment of machine/deep learning models as well as the use of remote sensing data You must have relevant experience in the development of hydrodynamic and water
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strong need for accurate monitoring and forecasting of the Earth. Machine learning and signal processing play important roles here. The PhD project will focus on machine learning and signal processing
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relevant background within control, building, or HVAC engineering. A background in applied mathematics can also be relevant if there is a strong focus on data-driven modeling, machine learning, and control