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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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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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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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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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of realistic inflow environments and their impact on turbine performance Assessment of clearance effects on loads and efficiency near the sea surface and seabed Development and use of multi-fidelity models
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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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both water tanks and with phase change material - PCM). Digital twins of the system for real-time decisions, based on petroleum field experience. LCA and economic conciderations. Modeling and reservoir
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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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approach of data-driven membrane discovery that includes material space construction and exploration, candidate selection and verification, providing data for machine learning models to optimise membrane
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. About the project The current project is aiming at developing novel human models for childhood dementia CLN3 to recapitulate disease progression and explore novel promising gene therapy strategies