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expertise in HCI and education, including adaptive gamification, engagement, learning analysis, and the design of motivational affordances in education. As part of the project, the PhD student will work with
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, we develop kinetic models, but these models are reliable only for operating conditions quite close to the optimum production conditions and in isothermal conditions. By working at isothermal conditions
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and with the 2AT team at Institut Pprime to develop resolvent-based modelling tools for turbulent jets in cases where the jet mean flow is three-dimensional. The researcher shall: - Develop a high-order
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and with the 2AT team at Institut Pprime to develop a shape-optimisation tool based on resolvent analysis, applied to landing-gear aeroacoustics The researcher will develop a numerical methodology based
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and with the 2AT team at Institut Pprime to develop an innovative jet-noise prediction tool. The researcher will develop a novel jet-noise prediction tool based on a resolvent analysis of the Navier
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technologies within our laboratory. - Design and develop processes for synthesizing hollow fiber membranes to meet the specific needs of our research and development projects. - Design and develop processes
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purely correlational analyses and to develop predictive models with operational relevance. Where to apply Website https://emploi.cnrs.fr/Candidat/Offre/UMR8212-DAVFAR-008/Candidater.aspx Requirements
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The expert will participate in the necessary methodological developments and analyses of airborne data recorded by the IAGOS research infrastructure (https://www.iagos.org ) and from other networks, to provide
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evaluation of modal-decomposition techniques applied to data from high-fidelity numerical simulations of landing-gear aeroacoustics. The researcher will develop and implement modal-decomposition methods using
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applies to protocols using "short" codes, where these codes have a non-negligible probability of being guessed by an attacker. The goal of this postdoctoral research is to develop new methods