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Field
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• Conduct computational fluid dynamics (CFD) simulations • Conduct experiments in wind tunnels and water channels • Conduct field measurements • Analyze experimental and simulation data
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carbon cycle dynamics, paleoclimate, and fluid-rock interaction. We seek individuals with research programs who can bridge existing research foci in hazards, energy, resources, and climate within
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absorption in gasification of biomass. The overall approach is lab-scale experiments in combination with Computational Particle Fluid Dynamic (CPFD) model development. The person appointed will be affiliated
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The School of Mechanical & Aerospace Engineering (MAE) is a robust, dynamic and multi-disciplinary international research community comprising of world-class scientists and bright students. MAE
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Posting Description POSTDOCTORAL ASSOCIATE, Chemical Engineering, in the area of complex fluids and ionic liquids, will work under the direction of Professor Maggie Qi to establish a coarse-grained
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PhD in Computational Simulations of Turbulent Reaction Flows for Clean Energy and Sustainable Propul
the preparation of a doctorate, contains: Research: The FLOW research group is a young, dynamic group working in the fields of thermodynamics, fluid mechanics, and data-driven modelling. At the Department
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Status Full-time Hours Per Week 39.10 Offer Starting Date 1 Oct 2026 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within
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. Candidates with expertise in aerospace structures and mechanics are encouraged to apply. Areas of interest include, but are not limited to, structural and nonlinear dynamics, aeroelasticity, fluid-structure
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The University of Manchester has a strong history of research into offshore renewable energy, with leading international activity in wave hydrodynamics and computational engineering. We are here
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Inria, the French national research institute for the digital sciences | Rennes, Bretagne | France | 2 months ago
for model noise can fundamentally disrupt the corresponding fluid dynamics models, leading to unrealistic properties. Rigorously justified methodologies for deriving stochastic dynamics models have been