Type de recrutement
Stage
Durée
Urgent
oui
Rattachement
Cedric
Fin de l'affichage
Détails (site web)
Détails (fichier)
This internship aims at developing a hybrid methodology that unifies model-based observers (affine observers, high-gain observers, Unknown Input Observers (UIOs), interval observers, etc.) with machine learning methods (generative models, latent-state networks, hybrid architectures) in order to provide robust, explainable, and uncertainty-quantified state estimation.
Expected areas of expertise:
Strong background and interest in the interaction between control theory, applied mathematics, and artificial intelligence. Programming skills in MATLAB and/or Python are required.
Application:
Curriculum vitae, motivation letter, and academic transcripts (M2 and, if applicable, previous degrees).
Contacts:
- Thach Ngoc Dinh, Associate Professor (ngoc-thach.dinh@lecnam.net)
- Jae Yun Jun Kim, Associate Professor (jae-yun.jun-kim@ece.fr)
