The doctoral program part of the École Doctorale 364 “Sciences Fondamentales et Appliquées” (ED.SFA) provides an advanced studies track for future researchers in numerical algorithms and data science for mechanics-physics.
It covers a wide range of subjects including:

  • high-performance linear algebra,
  • massively parallel mesh algorithms,
  • numerical methods for turbulent multiphase flows and fluid-structure interaction,
  • development of computational code scalable on supercomputers,
  • data-intensive computing with deep learning and assimilation techniques.

In the context of the convergence between High-Performance Computing and Data Science, the development of computational tools combining numerical simulation and learning is crucial to accompany industrial partners in their digital transition.

The possibilities are numerous: data-driven models using offline simulation results or experimental results, reduced order models, deep-learning techniques for fast prediction, or optimization/control of industrial processes…

Water entry of yield-stress droplets, Anselmo Soeiro Pereira – CFL Team


Located at Sophia-Antipolis, research teams and students benefit from the support of MINES Paris | PSL University and Université Côte d’Azur, as well as collaboration with other institutes and industrial partners.