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Inria, the French national research institute for the digital sciences | Toulouse, Midi Pyrenees | France | about 2 months ago
-physical interactions between aerodynamics, propulsion, structures and materials. The systematic verification and validation of these models allows to integrate CFD in the certification process, reducing our
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oriented, regionally anchored top university as it focuses on the grand challenges of the 21st century. It develops innovative solutions for the world's most pressing issues. In research and academic
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of Antwerp. See also: https://remotesensing.vito.be/news/sspirit-tackling-plastic-pollution The main task of the KU Leuven PhD project will be the further development and validation of a two versatile
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. To investigate the Space Launch Impact on Climate and Environment, SLICE will therefore develop a research and training programme that bridges the current divide between space engineering and climate science to
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oriented, regionally anchored top university as it focuses on the grand challenges of the 21st century. It develops innovative solutions for the world's most pressing issues. In research and academic
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to wind catching system for the development of a 40 MW multi-rotor wind turbines, made of 40x1MW rotors (Link https://www.offshorewind.biz/2025/01/28/norway-grants-eur-100-million-to-deploy-multi-turbine
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for calculations developed with system codes (e.g. TRACE), as well as for new applications that are beginning to emerge with computational fluid dynamics (CFD) codes. Where to apply Website https://www.upv.es
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Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Help push the boundaries of urban wind modelling by developing efficient
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Development of a numerical tool for assessing radon prevention and mitigation methods in energy-efficient new buildings and existing buildings A PhD position is available in the Department of Physics
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applications. To achieve this, you will employ computational fluid dynamics (CFD) and machine learning (ML) to investigate degradation mechanisms under various operating conditions and develop strategies