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Field
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modeling to create a predictive tool that spans orders of magnitude in length and time. Hands-On Numerical Modeling: Implement your model in a custom-made data analysis tool that uses advanced optimization
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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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. The candidate must hold a PhD in mechanical engineering, aerospace engineering or a related field. The candidate must have a proven experience in numerical simulation in fluid mechanics and/or aeroacoustics, as
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | 6 days ago
walls; iii) Experimental and/or numerical characterisation of the mechanical and seismic behaviour of the proposed connection solutions; iv) Development and calibration of numerical models representative
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for the turbomachinery design optimization process conducted by a parallel PhD student at LMFA. The numerical solver involved is ProLB. It is an innovative Computational Fluid Dynamics (CFD) software solution developed
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on the candidate’s interests, the project may include field investigations (e.g., paleoseismological trenching, sediment core analysis) and/or numerical modeling of tectonic–erosion–sedimentation interactions. Where
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, 157, 2026. https://doi.org/10.1016/j.ndteint.2025.103531 It is strongly advised to contact the PhD supervisors before submitting your application. Where to apply Website https://amethis.doctorat.org
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numerical approach The PhD is part of a Franco-German co-funded project between IFP Energies Nouvelles (IFPEN) at Lyon and the Hamburg University of Technology (TUHH), focusing on the modelling of gas/liquid
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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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for a full-time, on-site PhD position in machine learning, forecasting and time series analysis. Reykjavik University, Department of Engineering. Duration: 3 years. Start date: Negotiable. Reykjavik