Damien FOURNIER

Summary

Education

  • 2008-11: Ph. D. in applied mathematics CEA Cadarache / Aix-Marseille University
  • 2005-08: ENSIMAG Computer Sciences and Applied Mathematics Engineering School
    Speciality: Modeling and scientific computation
  • 2007-08: University Joseph Fourier, Grenoble
    Master 2 on Applied Mathematics

Experiences

  • 2017- : Researcher Max Planck Institute for Solar System Research, Göttingen, Germany
    • Forward modeling: propagation of waves in a stratified medium
    • Inverse problem: linear and nonlinear methods
  • 2012-2016 : Postdoc Institute for Applied Mathematics, Georg-August-University, Göttingen, Germany
    SFB 963, project A1: "Solar turbulent convection probed by helioseismology"
    • Noise estimation for travel times and product of travel times
    • Data analysis to infer velocity correlations and Reynolds stresses
    • Development of new linear inversion methods for helioseismology
  • 2011-12: Assistant associate professor, Aix-Marseille University
    • Introduction to computer sciences for L1 students (lecture 16h, exercises 32h)
    • Applied mathematics in biology for L1 students (exercises 10h)
    • Algebra for L1 students (lecture 20h, exercises 40h)
    • Analysis and topology for L2 students (exercises 55h)
  • 2008 - 2011: Ph. D. thesis in applied mathematics, CEA Cadarache & Aix-Marseille University
    Adaptive mesh refinement methods for the Boltzmann equation
    • Derivation of error estimators adapted to the problem
    • Implementation of an adaptive mesh refinement method in an industrial code
  • 02-08/2008: Master thesis, CEA Cadarache
    A discontinuous Galerkin wavelet-based method to treat the autoprotection phenomenon in neutronics
    • Replace the linear representation of the energy dependence of the particle cross-sections by a wavelet decomposition
    • Method to select the wavelet coefficients and test on real data
  • Summer 2007: Internship, Centre de Technologie - Laboratoire Turbines (ALSTOM Power Hydro Grenoble)
    Optimization of a signal processing software

Technical skills

  • Programming: Java, C/C++, Python, Matlab.
  • Mathematics: Inverse problem, PDE, optimization, wavelets, data analysis.
  • Helioseismology: Time-distance helioseismology, solar oscillations, supergranulation, turbulence.
  • Teaching: Lecturer and teaching assistant, co-supervision of bachelor and master students and of a Ph. D. candidate.

Languages

  • French: native
  • English: fluent
  • German: intermediate
  • Spanish: intermediate