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include: Modelling and simulation of hybrid-electric aero-engine performance and environmental impact Working with preliminary system design and mission analysis Participating in and contributing
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 27 days ago
/Description: The Miao Lab in the Computational Medicine Program and Department of Pharmacology at the University of North Carolina – Chapel Hill (https://www.med.unc.edu/pharm/directory/yinglong-miao/) is
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and document criteria for drone communications simulator solutions and the datasets that are used to train and test them. - Prepare industry landscape identifying long-range communications, mesh
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laboratoire. L'algorithme final a montré de très bons résultats sur des données de simulations et sur des données expérimentales (https://doi.org/10.1364/OL.566273 ). Cependant, cette approche requière une
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you often find yourself fascinated by the multiscale complexity of real-world engineering problems? In this project you will develop advanced multiphase transport models for porous systems, bridging
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simulated and measured results to assess quantities of interest. Interface with world-class exascale computing clusters. Work with a dynamic team of researchers, developers, experimentalists, and model
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of Environmental Engineering, ETH Zürich and matriculate in ETH Zürich. The research is related to development of experimental and modeling techniques to identify emission sources, simulate the airborne transport
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On Brain Disorders. The successful candidate will join us (fixed-term 3 years, 100% FTE contract of employment) to develop computational models of the neonatal brain, working on the intersection
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simulations); developing and maintaining tools for data processing, visualisation of results and automation of computational experiments; optimising code performance and supporting the integration of models
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biology approaches to simulate biological models at different time-scales in the context oft the development of the PhysiCell/PhysiBoSS modelling systems(Ponce-de-Leon et al., 2023). In particular, we