Type annonces : Proposition de poste

[PhD] Explainable Deep Learning for Early Identification of Neurodevelopmental Alterations through the Analysis of Cardiac Autonomic Regulation

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Starting date: October 2026Application deadline date: March 20th, 2026Final decision date: June 4th, 2026Contact: hugues.patural@univ-st-etienne.fr, olivier.alata@univ-st-etienne.fr Position Overview This PhD project corresponds to a fully funded 3-year doctoral position within the framework of the Doctoral School EDSIS. The thesis will be conducted at Université Jean Monnet, Saint-Étienne, France, with an…

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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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[PhD] Détection de signaux faibles en contexte volcanique tropical : Apprentissage profond et traitement avancé du bruit électromagnétique

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Mots clés : Estimation robuste du signal MT, deep Learning interprétable, traitement adaptatifen contexte bruité, séries temporelles multivariées, suivi électromagnétique des volcans Résumé : L’exploitation des données magnétotelluriques (MT) en contexte fortement bruité reste un défi scientifique majeur, en particulier pour la détection de signaux faibles associés aux dynamiques profondes…

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[StageM2] Self-Supervised Learning for Epilepsy Detection Under Limited Data

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Telecom SudParis (IP Paris), France Background Epilepsy is a chronic neurological disease that poses significant challenges to patients and their families, as such, effective detection and prediction of epilepsy can facilitate patient recovery, streamlining healthcare processes [1]. To perform this detection process, machine learning based methods, with recently deep learning…

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[StageM2] Internship in Quantification for Radio-Astronomy

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Recruit a end of study engineer or Master 2 student in electronics or computer science. The aim of this internship is to explore the potential energy and latency benefits of quantification in radio astronomy imaging. Keywords: quantification, radio astronomy, high-performance computing, energy, optimization Context Radio-interferometers image the sky in radio…

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