PhD offers | MSc in Industrial and Applied Mathematics - Grenoble

Deep Multimodal Image Fusion for Scientic Imaging

Thu, 18 Jun 2026 00:00:00 +0000

Reconstruction de champs et identification de source dans les écoulements de polluants en milieu ventilé par apprentissage profond informé par la physique

Thu, 18 Jun 2026 00:00:00 +0000

Co-design of Physical Acquisition Systems and Computational Reconstruction for Scientic Imaging

Wed, 17 Jun 2026 00:00:00 +0000

Development of novel and effective Arbitrary-Lagrangian-Eulerian ADER Finite Volume and Discontinuous Galerkin schemes on moving 3D polyhedral meshes

Sun, 12 Apr 2026 00:00:00 +0000

Modélisation par éléments finis sous FreeFem de la détection électrochimique de micropolluants

Sat, 24 Jan 2026 00:00:00 +0000

Tensor-Based approaches for non-Intrusive Load Monitoring of French households

Mon, 12 Jan 2026 00:00:00 +0000

théorie minimax pour les contraintes de forme et de régularité

Sat, 11 Oct 2025 00:00:00 +0000

Ce sujet de thèse en statistiques mathématiques, financé, devrait probablement être mis au concours de l’école doctorale pour un démarrage en septembre 2026. Il s’adresse aux étudiants de niveau M2 ayant un solide parcours en mathématiques et souhaitant s’intéresser à la théorie des statistiques.

Wave propagation in random media and Monte-Carlo methods: interactions be- tween surface and bulk waves for applications in mechanical engineering

Sun, 29 Jun 2025 00:00:00 +0000

Recent advances in neuroscience and machine learning have revitalized interest in models of noisy cognition, which depart from the classical view that decisions result from stable preferences. Instead, these models attribute behavioral variability to systematic limitations in cognitive processing. This framework has gained particular traction in the study of decision-making under risk and uncertainty, offering explanations for well-documented behavioral regularities, such as risk aversion, loss aversion, and probability weighting. In this project, we aim to extend the cognitively grounded models to simple strategic interactions, including social dilemmas, coordination problems, and bargaining/trust games, and then to design and implement behavioral experiments to empirically test the predictive validity of these models against traditional utility-based models.

Imperfect Cognition in Strategic Choices -- Theory and Experiments

Mon, 19 May 2025 00:00:00 +0000

Unforeseen contingencies in Human and Machine Learning -- Theory and Experiments)

Mon, 19 May 2025 00:00:00 +0000

In standard models, agents are assumed to have an exogenously given correct model of the underlying uncertainty. In practice, the “correct model” is rarely known and has to be inferred from data. Both humans and AI-decisions makers may experience surprises and have to take into account “unknown unknowns”. This project studies the way in which humans and machines derive the relevant model of uncertainty from available data in view of possible unforeseen contingencies. The goals of the project are three-fold: derive and study an axiomatic model of decision making under uncertainty, applicable to both human and machine-learning. Use the model to generate behavioral and normative predictions, as well as to study learning and the value of information acquisition in such environments. Design an experiment to test the theoretical predictions using human subjects and AI-algorithms.

Design of experiments and multi-fidelity for regional climate simulations

Tue, 22 Apr 2025 00:00:00 +0000

Machine Learning pour l'identification optique de pathogènes bactériens

Tue, 25 Mar 2025 00:00:00 +0000

Détection non-supervisée d’anomalies dans des flux continus de séries temporelles multivariées

Wed, 29 Jan 2025 00:00:00 +0000

Statistical geometry for the spatiotemporal modeling of compound climate events

Tue, 28 Jan 2025 00:00:00 +0000

Détection et localisation de cibles masquées en milieu urbain

Tue, 21 Jan 2025 00:00:00 +0000

Synthèse de formes d'onde Radar et communications par réseau MIMO

Tue, 21 Jan 2025 00:00:00 +0000

Analyse théorique et numérique des fuites dans les réseaux d’eau potable à partir de la propagation d’onde de pression en leur sein

Fri, 20 Sep 2024 00:00:00 +0000

Modélisation numérique et validation expérimentale de la fragmentation d’un verre trempé par une approche champ de phase

Tue, 03 Sep 2024 00:00:00 +0000

HYBRID PHYSICS- AND DATA-DRIVEN METHODS FOR X-RAY FLUORESCENCE COMPUTED TOMOGRAPHY (XRFCT)

Fri, 28 Jun 2024 00:00:00 +0000

Active learning with functional inputs: application to wind turbine reliability design

Fri, 07 Jun 2024 00:00:00 +0000

3D Transcranial Ultrasound Localization Microscopy (ULM) via Inverse Problem Solving

Mon, 03 Jun 2024 00:00:00 +0000

Allocation de ressources pour les réseaux sans fil sécurisés militaires

Sun, 19 May 2024 00:00:00 +0000

Supervised Leverage Scores for Large-Scale Statistical Learning

Tue, 09 Apr 2024 00:00:00 +0000

Neural Implicit Representation and operator learning for mutliscale problems in physics

Tue, 19 Mar 2024 00:00:00 +0000

Floating wind farms layout optimization for energy production improvement

Sat, 09 Mar 2024 00:00:00 +0000

Développement d’un jumeau numérique pour la prédiction de la durée de vie résiduelle de réservoirs de stockage d’hydrogène

Fri, 16 Feb 2024 00:00:00 +0000

Physics-informed Machine Learning for Defect Detection in Medical Microbatteries

Wed, 31 Jan 2024 00:00:00 +0000

New architectures in inverse geometry for spectral X-ray imaging

Mon, 08 Jan 2024 00:00:00 +0000

Resin Flow Modeling in Deformable Fibrous Media

Sun, 07 Jan 2024 00:00:00 +0000

Apprentissage machine et réseaux de convolution interprétables pour le débruitage supervisé et non-supervisé d'images : application à l'imagerie satellitaire

Thu, 21 Dec 2023 00:00:00 +0000

Computational methods for hidden semi-Markov models with mixed effects -- application to plant and root branching patterns

Thu, 22 Jun 2023 00:00:00 +0000

Identification de modèles d’équations différentielles à partir de séries temporelles en microéconomie, physiologie végétale et énergie solaire

Tue, 06 Jun 2023 00:00:00 +0000

Modélisation électromagnétique de dispositifs d’électronique de puissance par la méthode PEEC accélérée par compression tensorielle à faible rang

Thu, 01 Jun 2023 00:00:00 +0000

Identification of rheological parameters by physics in- formed neural networks. Application to granular media

Thu, 18 May 2023 00:00:00 +0000

Analyse Numérique et Asymptotique de l’Interaction de Structures photoniques et quantiques via un champ électromagnétique

Fri, 28 Apr 2023 00:00:00 +0000

Investigating model mis-specification in simulation-based inference

Sat, 22 Apr 2023 00:00:00 +0000

Security of decentralized deep learning -- integrity and confidentiality of embedded deep neural network model

Sat, 22 Apr 2023 00:00:00 +0000

In the context of research actions in the field of the Security of Artificial Intelligence, we propose the following PhD subject : Security of decentralized deep learning : integrity and confidentiality of embedded deep neural network models

Context

Large-scale deployment of AI
New decentralized training processes
Model security : a complex attack surface -Very active scientific community: Adversarial Machine Learning / Privacy-Preserving Machine Learning (main actors : Google, Meta, MIT, Stanford, Toronto, Tubingen, ETH, …)

Objective

Definition of the different threats models for embedded and decentralized training (focus on Federated Learning)

Caracterization of attacks targeting models integrity, availability and confidentiality of models and data.
Improve and propose protection schemes
Propose evaluation methods for model robustness

contact : pierre-alain.moellic@cea.fr

Méthodes numériques pour le roulage stationnaire

Sat, 15 Apr 2023 00:00:00 +0000

Floating wind farms layout optimization for energy production improvement

Tue, 21 Mar 2023 00:00:00 +0000

Uncertainty analysis in a windfarm based on wind datas"

Tue, 21 Mar 2023 00:00:00 +0000

Computational methods for hidden semi-Markov models with mixed effects -- application to plant and root branching patterns

Tue, 14 Mar 2023 00:00:00 +0000

Impact modeling and measurement of adverse weather conditions using computer vision

Thu, 02 Feb 2023 00:00:00 +0000

Sparse Control

Thu, 02 Feb 2023 00:00:00 +0000

Computational Fluid Dynamics to infer embryonic tissue rheology

Wed, 21 Dec 2022 00:00:00 +0000

PhD opportunities in Mathematical Sciences

Wed, 21 Dec 2022 00:00:00 +0000

Apprentissage automatique et profond appliqué à la détection robuste de cibles radar