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Field
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the field of fluid mechanics, multiphase flows, thermodynamics and heat exchange, laser measurement techniques, machinery dynamics, tribology and diagnostics of energy production machinery. The thematic
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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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Particle Fluid Dynamic (CPFD) model development. The person appointed will be affiliated with the Research Group in Energy and Environmental Technology (URGENT). Duties Complete the doctoral programme up
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, scientific programming, microfluidics, or microfabrication would be an asset. Theoretical or numerical knowledge of fluid mechanics would also be appreciated. Where to apply Website https://emploi.cnrs.fr
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sequence and to model the evolution of body size using bounded evolutionary models. 3) Biomechanical and Hydrodynamic Modeling: Apply computational fluid dynamics to test hydrodynamic hypotheses related
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inclusion—whether more or less viscous than the surrounding fluid—while noting a qualitative dependence on the flow type. The aim now is to explore mixing between two comparable masses (or volumes), focusing
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LPMS plant at a SIT Punggol campus Assist in carrying out of experiment, data logging and analysis of data collected. Work with computational fluid dynamics (CFD) results generated by an expert
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Requirements Research FieldEngineeringEducation LevelPhD or equivalent Skills/Qualifications Technical Background: PhD in aeroacoustics for wind turbines. Required knowledge: Computational Fluid Dynamics
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robotics, mechatronics, mechanical system design, programmable logic controllers (PLCs), dynamics, intelligent thermal-fluid systems, etc. Strong written and verbal communication skills are required
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Inria, the French national research institute for the digital sciences | Rennes, Bretagne | France | about 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