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Postdoc: Dynamic Calibration and Optimization Strategies for Subgrid-Scale Turbulence Modeling within the Framework of Lattice Boltzmann Simulations

Le 1 septembre 2025

14+months
Ecully, France

Contacts : emmanuel.leveque@ec-lyon.fr, lucien.vienne@ec-lyon.fr

The Laboratory of Fluid Mechanics and Acoustics (LMFA) is seeking a highly qualified postdoctoral researcher to contribute to the development of dynamic calibration and optimization strategies for subgrid-scale turbulence modeling within the framework of LB simulations of engineering flows.

The Lattice Boltzmann (LB) method is gaining strong interest in Computational Fluid Dynamics. While traditional methods rely on a discretization of the Navier-Stokes equations at a macroscopic level, the LB method considers the fluid at a kinetic level. Capturing the dynamics of collections of fluid particles distributed over a lattice is here preferred to solving non-linear PDEs. Processing a simulation in this way has some advantages. The low numerical dissipation allows for an accurate simulation of time-dependent flows. Furthermore, the high scalability on massively parallel computers can lead to advantageous turn-around times for industrial applications.

The successful candidate will be in charge of improving the turbulence modeling included in the ProLB software developed at LMFA with other academic and industrial partners. The Shear-Improved Smagorinsky Model is employed for large-eddy simulation of turbulent flows. The current implementation requires the definition of a cut-off frequency that represents a characteristic frequency of the simulated flow. The main focus will be in particular to propose a dynamic adjustment of this frequency by integrating machine learning techniques.

This research activity is part of a 3 years-long major project co-funded by the DGAC (French Civil Aviation) and directed by Airbus. The successful candidate will develop his research activity collaboratively with the other academic and industrial partners of the project.

Qualifications:
PhD in Engineering, Physics, Theoretical and Applied Mechanics, or Applied Mathematics
Contributions in the area of scientific computing and Computational Fluid Dynamics.
Prior Experience in Turbulence Modeling, Machine Learning or Lattice Boltzmann method would be an advantage.

Location:
Laboratoire de Mécanique des Fluides et d’Acoustique
CNRS UMR 5509
École Centrale de Lyon
36 Avenue Guy de Collongue
F-69134 Écully cedex France

Application: 
a detailed CV with a cover letter
a summary of recent work and interests
one or two letters of reference