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printing), enabling new design opportunities and advanced construction techniques. The research methodology combines theoretical modelling and experimental validation. The work will begin with an extensive
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of physics into machine learning and deep learning architectures to create accurate, physically consistent, efficient and interpretable/generalizable models. This PhD project will contribute to the development
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interested in programming and developing the next generation models for inflow forecasting? Work with us, SINTEF and the Hydropower industry to develop State of the art models for better water management. The
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conduct background checks on potential candidates. Please note that all our candidates may be asked questions necessary in this context. This includes questions about any connections to countries
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are offering a fully funded PhD position in the field of Physics-informed Learning-based Control. This interdisciplinary research area bridges control theory, machine learning, and physics-based modeling
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models to resolve blade loads and structural responses under both operational and extreme conditions, including scenarios with partial out-of-water exposure Uncertainty quantification to ensure robust and
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Technology » Energy technology Environmental science Computer science » Modelling tools Researcher Profile First Stage Researcher (R1) Positions PhD Positions Country Norway Application Deadline 31 Oct 2025
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. To enhance the security of the hiring process, Nord may conduct background checks on potential candidates. Please note that all our candidates may be asked questions necessary in this context. This includes
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of smart technologies to visualize yard operations in a digital form (such as virtual models and digital twins). Smart technologies can collect, analyze, and represent data from various sources
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access. The goals of such access include supporting registry operations as well as health care research. Of particular interest in this context are differentially private algorithms for statistical model