Propositions de stage

Pour proposer un stage, ou pour plus d’informations sur les stages, voir ici.

Research Internship Positions on Graph Machine Learning and Applications
CentraleSupélec
Fragkiskos Malliaros
When Learning Is Not Enough: Understanding Structural Limits in AI Agents
INSA Rouen
Aomar OSMANI
Learning Continuity under Conceptual Change: Foundations and Semantic Knowledge Preservation
INSA Rouen
Aomar OSMANI
Machine learning for biology: flow matching, optimal transport and experimental design (NYU, New York)
New York University
Romain Lopez
Theoretical Foundations for Third-Party Privacy Evaluation of Large and Opaque Models
Inria
Aurélien Bellet
Few-run privacy auditing: trading off computational cost and tightness
Inria
Aurélien Bellet
Hierarchical Temporal Credit Assignment for Online RNN Learning
Dauphine - PSL
Alexandre Allauzen
Decoding Strategies for LLMs: Continuous Optimization over the Simplex
Dauphine - PSL
Alexandre Allauzen
How many variables does a brain network need? (M2 internships in computational neuroscience)
Université Paris-Saclay
Yannaël Bossard
Apprentissage contrastif de dynamiques latentes identifiables pour la surveillance des équipements de radiothérapie
Université de Toulouse
Kélian Poujade Kélian Poujade
Bayesian Inverse Problem for Spatially Varying Anisotropy in Stochastic PDEs
AgroParisTech
Charlie Sire
Théorie des valeurs extrêmes appliquée à l’estimateur LogSumExp
ONERA
Jérôme Morio
The impact of spectral optimisation on mode collapse in generative models
ENS - PSL
Arthur Pellegrino
Transfer learning for Physics Informed Deep Learning to forecast water quality in lakes
INRAE
David Métivier
Modélisation générative conjointe des aléas du marché de l’électricité à moyen terme
ENS PSL, Dauphine PSL, EDF
Eddie AAMARI
Historical Wildfire Data for Conventional and AI-based Fire Spread Simulation, Prediction and Parameter Calibration
École nationale des ponts et chaussées
Sibo Cheng
Physics-Constrained Generative AI Modelling of Parametric Dynamical Systems
École nationale des ponts et chaussées
Sibo Cheng
Reinforcement Learning for Jackson Networks
CNRS
Gersende FORT
[AI for Science] Developing novel algorithms for the curiosity-driven exploration of fiber trajectories in structured microfluidic environments
Inria
Pierre-Yves Oudeyer
Electromyography-driven Robot MPC assistance behavior
Inria
Margot Vulliez
Problème inverse et simulation de métasurfaces par deep learning génératif
CEA
Mathys Le Grand
Impact of Quantization Bias in Large-Scale Kernel Regression
Université Grenoble Alpes
Antoine Chatalic
Metamodeling of propulsive jet infrared signatures using deep learning
ONERA Palaiseau
Sidonie Lefebvre
Adaptive Computing through Neuromorphic Artificial Intelligence for Intelligent Vehicles
Stellantis Group
Thomas Hannagan
Topology Preserving Dimensionality Reduction
Sorbonne Université
Julien Tierny
Use of AI agents to automate Monte Carlo calculations
CEA Cadarache
Achment Chalil
AI Internship
Synboli
Laura Misrachi