Stage M2/Ingénieur (+thèse) The full subject, including images and references, can be found at https://partage.imt.fr/index.php/s/4kZRXNwMfaZrscn Context The remote sensing field aims at exploiting satellite or aerial images for earth observation. This, in turns, has an increasingly important social impact, as the applications of these methods include tackling key challenges such…
Stage master Research team: RAP, Robotic department — LAAS-CNRS, Toulouse, FranceAdvisors: Maxime Escourrou (maxime.escourrou@laas.fr), Ariane Herbulot (ariane.herbulot@laas.fr)Duration: 4 — 6 monthsSchooling level: MasterStarting date: Flexible around March 2025 Keywords: Perception, Computer Vision, Data fusion, Robustness The aim of this internship is to evaluate the results of several object tracking methods…
Stage M2/Ingénieur Pansharpening is a fundamental and crucial task in remote sensing which generates a high-resolution hyperspectral image by fusing a low-resolution hyperspectral image and a high-resolution panchromatic (or multispectral) image. A range of methods formulate pansharpening as an inverse problem from which iterative algorithms are derived. Those methods depend…
Stage M2/Ingénieur L’équipe SAFE du laboratoire GREYC situé à Caen propose un stage de recherche d’une durée de 6 mois sur la génération de deepfake vidéos, sujet d’actualité notamment depuis l’utilisation des techniques d’apprentissage profond (deeplearning) et de GAN inversés. Les étudiants intéressés peuvent envoyer leur candidature à : Christophe…
Stage M2 Scientific Fields: Computer Vision, Industry of the Future Keywords: Foundation Models, 6D pose estimation, Digital Twin, Synthetic and Hybrid Dataset, Manufacturing environments Supervision Name Position, Title @ Nicolas Ragot Associate professor nragot@cesi.fr Vincent Havard Associate professor, HDR vhavard@cesi.fr Works Details of the tasks This M2 internship is part…
Postdoctoral position The aim of this postdoctoral research project is to develop deep learning models that integrate causal and correlation relationships, focusing on enhancing the explainability of AI systems. This research project could also be expanded to explore the application of diffusion-based generative models within the context of explainable AI….
CESI LINEACT recrute un.e ingénieur.e de recherche pour un contrat de 18 mois avec des compétences en apprentissage machine, vision par ordinateur et traitement d’images. Descriptif des missions Ce recrutement de type CDD 18 mois, s’inscrit dans le cadre du Challenge CoHoMa III proposé par le Battle Lab Terre et…
Stage M2 Internship supervisors: Eric Thiébaut, Michel Tallon @ : eric.thiebaut@univ-lyon1.fr, mtallon@obs.univ-lyon1.fr Address/Workplace: CRAL – site Charles André : 9 avenue C. André, St Genis Laval Hosting research team: AIRI Internship title: Adaptive optics control and learning Summary of proposed work: Context: Adaptive optics (AO) systems are used by most…
Stage M2 Internship supervisors: Olivier Flasseur, Eric Thiébaut, Maud Langlois @ : olivier.flasseur@univ-lyon1.fr, eric.thiebaut@univ-lyon1.fr, maud.langlois@univ-lyon1.fr Address/Workplace: CRAL – site Charles André : 9 avenue C. André, St Genis Laval Hosting research team: AIRI Summary of proposed work: Context: The direct observation of the close environment of stars can reveal the…
Stage M2 Link to the subject: https://images.icube.unistra.fr/img_auth_namespace.php/9/9f/M2_internship_ICube.pdf Context Macromolecular assemblies are large complexes of proteins involved in most cellular processes. The field of structural biology aims to decipher their molecular structure. In particular, the goal is to identify and localize the proteins inside the structure, in order to infer the…
