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Within this project, the Post- Doc researcher will develop advanced uncertainty quantification (UQ) methodologies for Multi-fidelity models in the context of computationally demanding Computational Fluid dynamics (CFD) simulations

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Academic year: 2022

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Title: Advanced Uncertainty Quantification Methods for Multi-fidelity models

A Post-Doc Position is opening at Inria Saclay Île-de-France. The Post-Doc will be hosted at the Center for Applied Mathematics (Ecole Polytechnique, CNRS, Inria) and founded by the MONNALISA project (EU-H2020-CS2).

The MONNALISA project intends to provide an accurate, physics-based low-order model for predicting the nonlinear behavior of tailplanes to enable nonconventional rear ends optimization for the next-generation of Large Passenger Aircraft. Within this project, the Post- Doc researcher will develop advanced uncertainty quantification (UQ) methodologies for Multi-fidelity models in the context of computationally demanding Computational Fluid dynamics (CFD) simulations.

The candidate should have strong backgrounds in applied mathematics and scientific computing. An experience with uncertainty quantification methods or CFD will be a plus.

Applicants holding a Ph.D. in Applied Mathematics, Computer Science, Data Science, Mechanical Engineering, or other relevant areas should submit their curriculum vitae electronically, with three reference contacts and copies of (up to three) selected publications.

The expected starting date is January 2021, with an overall duration of 24 months.

Minimum monthly gross income (depending on experience): 2653 euros.

Contact information:

PM Congedo ([email protected]), O. Le Maître ([email protected]) Bâtiment Turing

1 rue d’Estienne d’Orves 91120 Palaiseau

France

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