Job offers

Internships

Semantic Analysis of Texts and Images

To apply, let refer to the contact information within each internship proposal

List of internships LASTI-2025:
– Using Large Language Models for Few-shot Entity and Relation Extraction in Scientific Articles on New Material Design
– Information extraction from complex documents
– Spatio-temporally controlled visual content generation
– Few-shot Named Entity Recognition
– Injecting Symbolic Knowledge into Zero-Shot and Few-Shot Large Language Models
– Frugal learning and adaptation of textual generative models
– Toward robust fact checking in domain-specific news
– Evaluation de la fiabilité et de la robustesse des grands modèles de langue (LLMs) sur des tâches d’annotation dans le domaine médical

Computer Vision and Machine Learning for scene understanding

To apply, send an email with your resume and a motivation letter to lva-stages@cea.fr

LVA-25 : List of internship subjects
S1 : Image Editing via Natural Language for Complex Scene Representation
S2 : Object detection by parametrization using elementary 3D shapes
S3 : Open-Set Object Detection: Can VLM understand all of the unknown world?
S4 : Motion Guided Object Discovery
S5 : Video Anomaly Detection and Understanding
S6 : Develop an MLOps stack
S7 : Label Efficient 3D Detection with Foundation Models
S8 : Enhancing Visual Reasoning in Vision-Language Models (VLMs) through Dynamic Visual Feature Selection
S9 : Multi-view re-identification of objects and individuals based on 3D representation
S10: AI-Driven Data Collection and Continuous Model Improvement for Robotic Applications

Vision for modeling and localization

LVML-24: Liste des sujets de stage (cliquer pour les détails):
– Détection d’anomalies images dans des objets par apprentissage profond sur peu de données
– Apprentissage par démonstration : robot-vision
– Saisie robotique pluri-digitale d’objets sur la base de cartes d’affordances estimées par réseau de neurones
– Certification et robustesse des réseaux de neurones
– Compression des architectures d’IA
– Apprentissage profond et imagerie hyperspectrale
– Approche neurale pour la reconstruction & la localisation 3D d’objets déformables
– Relocalisation à l’aide du champ magnétique ambiant et calibration simultanée du magnétomètre

PhD positions

Computer Vision and Machine Learning for scene understanding

Job offers

Computer Vision and Machine Learning for scene understanding