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differential equations, Excellent oral and written communication skills. Prior experience in computational fluid dynamics or active matter will be a big advantage, but we seek, above all, a willingness to engage
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of fluid mud. The project combines mathematical model development, nonlinear dynamical systems analysis, turbulence modelling, and environmental fluid mechanics. The successful candidate will contribute
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, Applied Physics, Process Technology, Civil Engineering or a closely related discipline) You have received training in multiphase flow physics, numerical methods, and computational fluid dynamics (CFD
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, numerical methods, and computational fluid dynamics (CFD), ideally complemented by application in your MSc thesis, research projects, or internships. Have excellent communication skills and command of English
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SINTEF Ocean; FME Martrans https://martrans.no/ and the Norwegian Maritime AI Centre https://www.ntnu.edu/mai The research is foreseen to focus on fluid-dynamic properties of the different sail types
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total appointment, averaged over the course of your PhD. Job requirements The successful candidate has the following qualifications: An MSc. degree in systems and control, fluid dynamics wind energy
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. Job description The Aerodynamics group is composed of 12 scientific staff and hosts the Chairs of Experimental Aerodynamics, Computational Fluid Dynamics and Flow Control. The group has a specific
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PhD in Advanced Testing, Modelling, and Simulation of Composite Materials under High Velocity Impact
the scientific understanding of composite materials under extreme dynamic loading. Your immediate leader will be Professor Tore Børvik, group leader of SIMLab. Duties of the position Complete the doctoral
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, targets the conversion of intermittent electricity to platform chemicals and fuels making use of dynamically operated processes. This is a promising route to alleviate net congestion and make more effective
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Computational Fluid Dynamics (CFD) has become indispensable for aerospace design, many important problems—including high-fidelity flow simulations, uncertainty quantification, and multidisciplinary optimization