Type annonces : Postes Stagiaires

[StageM2] Uncertainty quantification for image restoration. Application to Landsat-8 image recovery for analysis of river dynamics

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Key-words : Model-based neural networks, image reconstruction, uncertainty quantification,Markov Chain Monte Carlo, variational Bayesian methods, proximal algorithms. Localisation : Laboratoire de Physique de l’ENS Lyon46 allée d’Italie, 69007 Lyon Supervisors : Nelly Pustelnik, DR CNRS, ENS Lyon (nelly.pustelnik@ens-lyon.fr)Barbara Pascal, CR CNRS, Encole Centrale Nantes (barbara.pascal@cnrs.fr)Laurent Jacques, Prof. UCL et ENS…

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[StagePFE/M2] Adaptation proactive du MCS en 5G ferroviaire par co-simulation MATLAB–Simu5G et Machine Learning

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Mots clés : 5G/6G, FRMCS, mobilité ferroviaire, SINR/BLER, HARQ, AMC, Machine Learning, co-simulationMATLAB–Simu5GDurée : 6 moisLieu : IMT Nord Europe – Campus de Lille / Villeneuve-d’AscqEncadrants : Dr. Yahia Medjahdi et Dr. Wajdi Elleuch (IMT Nord Europe, CERI-SN) Contexte :Avec l’arrivée du FRMCS (Future Railway Mobile Communication System), les trains…

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[StageM2] – Détection automatique des défauts de soudage par analyse de signaux et apprentissage machine

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Alfa Laval Golbey est une société reconnue pour son savoir-faire dans le dimensionnement et la fabrication d’échangeurs de chaleur compacts destinés à la distillation des gaz, de l’air, au traitement des hydrocarbures et à la production d’hydrogène. Ce savoir-faire s’exprime plus particulièrement dans la façon de concevoir et de réaliser…

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[StageM2] Predicting water quality in watersheds and rivers using deep learning methods

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Laboratory: IMT Nord Europe, CERI Systèmes Numériques, Lille, France Duration: 6 months Supervisors: Christelle Garnier and Anne Savard Context: The water quality in watersheds and rivers is a crucial issue for the environment, human health, and economic development. The main sources of water pollution are varied: agricultural activities, industrial discharges,…

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[StageM2] Machine learning-based anomaly detection for environmental time series

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Laboratory: IMT Nord Europe, CERI Systèmes Numériques, Lille, France Duration: 5 months Supervisors: Christelle Garnier and Anne Savard Context: Air pollution monitoring, along with various environmental time-series measurements such as heat waves, rainfall or snowfall, noise and humidity, plays critical role in evaluating trends and impact on human well-being worldwide….

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[StageM2] Analysis of imaging statistical performance for synthetic-aperture observation systems

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Scientific context Synthetic Aperture Radar (SAR) imaging has become an essential remote-sensing modality to obtain high-resolution images in all-weather, day-and-night conditions (Soumekh, 1999). Modern SAR systems are increasingly used in applications such as Earth observation, surveillance, environmental monitoring, among others. As SAR technology evolves toward higher resolutions and more complex…

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