• Development

    Scientific Computing : Expert in Fortran (77, 90), good practical understanding of c# and Visual Studio

    Processing : Expert in Python, Matlab; good practical understanding of R

    Scripting : Expert in shell scripting, Latex

    Machine Learning : using scikit-learn and keras Python library, Tensorflow.

    Data management : NetCDF, GRIB

    Version Control System: SVN, Git

    Mesh generator : SMS, xmGredit

    Others : Knowledge of SQL, Scilab, gdal, Perl, c++, VB, html, IDV, ncl, CDO

  • High Performance Computing

    Strong knowledge / experience of HPC clusters (daily use since 2006).

    Good knowledge of MPI

    Knowledge of OpenMP

  • Mathematical Modelling

    Regular, curvilinear and unstructured grids.

    Finite differences, finite elements and finite volume methods

    Sigma, S, Z and hybrid vertical system of coordinates; LSC2 (Localized Sigma Coordinates with Shaved Cell)

    Eulerian Lagrangian Methods

    Machine Learning (2 weeks introductory course by Yandex School of Data Analysis)

  • Modelling Codes developer / user

    Wave models : SWAN, WaveWatchIII

    Circulation models : NEMO, SCHISM, ROMS, MITgcm, ELCIRC, SELFE, MARS 2D, ADCIRC, MIKE21, TELEMAC

    Sediment transport models : SAND2D, a full model developed during the PhD, SISYPHE

    Atmosphere models : WRF

    Coupled systems : COAWST (WRF-ROMS-SWAN)

  • Environments

    Unix (Linux), Macintosh, Windows