4 master positions at IFP Energies nouvelles (IFPEN)

PhD in Applied Mathematics: Neural Linear Solvers and Preconditioners for General Sparse Matrices

. The objective of this work is therefore to accelerate the convergence of preconditioned linear system resolution through Machine Learning. Two main approaches will be investigated especially for the coarse

Acceleration of Newton-like methods for nonlinear systems by preflattening techniques

the original one, even though this is generally observed in numerical experiments. This is because, in the linear case, it is the conditioning of the matrix that governs the rate of convergence of the linear

PhD in Data Science: Real-Time Data-Driven Modeling of Road Traffic Pollutant Emissions and Atmospheric Concentrations at an Urban Scale

Guillaume SABIRON Requirements Research FieldComputer science » Modelling toolsEducation LevelMaster Degree or equivalent Skills/Qualifications Master's degree in Data Sciences, Fluid Mechanics or Applied

PhD position at IFP Energies nouvelles (IFPEN) in Earth sciences, geomechanics Graded damage approach for modelling of fractured regions in subsurface

regularized model in which a local damage law is augmented via convex constraints of non-local type. The main purpose of the PhD thesis is to extend the graded damage framework to deal with damage of porous