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), IBPS, Sorbonne Université. The team possesses expertise in developing application-specific microfluidic models that integrate desired mechanical conditions of fluid flow and substrate viscoelasticity
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simulation of reactive fluids, computational fluid dynamics) We particularly encourage applications from candidates with a computational background. What we offer Cutting-edge research in a dynamic work
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applicant must have (or be close to obtaining) a relevant PhD in Fluid Mechanics from an Engineering, Mathematics or Physics Department, a strong background in theoretical and computational fluid mechanics
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critical, to ensure expected engine performance is achieved. To predict this complex flow and heat transfer, next-generation Computational Fluid Dynamics (CFD) solvers using Large-Eddy Simulation (LES) and
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acquisition. Proficient writing of scientific documents (publications, reports, patents). Good communication skills combined with a synthetic mindset that allows for regular, fluid, and informative presentation
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enhances heat transfer without significantly increasing pressure losses, thereby improving the overall energy efficiency of the system. The project aims to deepen the understanding of the underlying fluid
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for donor kidneys. Central to this is the use of machine learning to evaluate the predictive value of biomarkers from various sources: donor-related data, perfusion fluid, and kidney biopsies. Kidney biopsies
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-edge sloshing research. Offer Requirements Education Level: Master’s degree (or equivalent) in Mechanical Engineering, Aerospace Engineering, Applied Physics, or a related field. Research Field: Fluid
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field. Research Field: Fluid dynamics, control engineering, or dynamical systems. Required Skills/Qualifications: Experience with experimental methods (laboratory setups, sensors, data acquisition
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model of high-pressure mechanical seals. Apply Computational Fluid Dynamics (CFD): Simulate gas film flow within the microscopic seal gap. Couple CFD with Structural Models: Study the fluid-structure