This page lists the propositions of internships we have received. Besides this list, we also encourage all the students to discuss directly with any other researcher, in order to find their own subject and supervisor.

Hybrid AI and CFD Approach for Simulating Droplet Impacts in Thermal Coatings, with Emmanuelle Abisset-Chavane, Cédric Le Bot and Stéphane Glockner.

Concentration of the geometry of empirical risks, with Paul Escande and Franck Iutzeler.

Towards more efficient kinetic and hybrid (kinetic-fluid) models and codes, with Claudia Negulescu and Nicolas Crouseilles.

Internships in Graph Machine Learning and Graph Neural Networks, with Nicolas Keriven.

Sensitivity Analysis for kernel testing with applications to Single Cell Genomics, with Bertrand Michel and Franck Picard.

Hybrid physics-AI model reductions with large dimensional parameter. Application to flood plain, with Jérôme Monnier and Robin Bouclier.

Testing for linear Hawkes process, with Manon Costa and Céline Duval.

Spatial Processes for Single-Cell Transcriptomics, with Jean-François Coeurjolly and Franck Picard.

Advanced numerical methods for solving dispersive equations, with Martin Parisot.

A study of the geometric phase of multivariate signals, with Nicolas Le Bihan, Pierre-Olivier Amblard and Julien Flamant.

Study of optimization problems to improve importance sampling, with Emilien Flayac and Florian Simatos.

Invariance of the plurigenera of projective manifolds of general type under holomorphic projective deformations, with Dan Popovici.

Sensitivity Analysis for kernel testing with applications to Single Cell Genomics, with Bertrand Michel and Franck Picard.

Internships in Graph Machine Learning, with Nicolas Keriven.

Online estimation of Sobol indices, stochastic miror descent optimisation algorithm, with Thierry Klein and Sébastien Gadat.

Asymptotic efficiency and global sensitivity analysis, with Thierry Klein, Agnès Lagnoux and Paul Rochet.

Iterated convolutions and the local limit theorem, with Jean-François Coulombel and Grégory Faye.

Super-linear spreading for Fisher-KPP equations set on antitrees, with Grégory Faye.

Multi-scale prediction of bike-share availability from open data, with Gaël Pallares and Myriam Foucras.

Geometry of Random Spatial Microstructures, with Yann Gavet.

Machine learning and phylogenetic networks for inferring the apple pangenome, with Charles-Elie Rabier and Kilian Raschel.

Weak metrics for gradient descent in seismic imaging by 1D full waveform inversion, with Ludovic Métivier and Clément Cancès.