Offre en lien avec l’Action/le Réseau : – — –/– — –

Laboratoire/Entreprise : LITIS Lab, Université de Rouen Normandie
Durée : 36 months
Contact : fannia.pacheco@univ-rouen.fr
Date limite de publication : 2026-11-18

Contexte :

Sujet :
See attached file for full description.

Keywords:
Self-Supervised Learning, Federated Learning, Time Series, Robustness, Frugal Feature Extraction, Anomaly / Out-of-distribution Detection

Supervisors:
Fannia Pacheco (fannia.pacheco@univ-rouen.fr)
Paul Honeine (paul.honeine@univ-rouen.fr)
Maxime Berar (maxime.berar@univ-rouen.fr)

Profil du candidat :
We are looking for a highly motivated candidate holding (or about to obtain) a Master’s degree or engineering diploma in applied mathematics or computer science, with a solid background in machine learning and strong programming skills in Python (PyTorch or equivalent). Prior exposure to time-series modeling, federated or distributed learning, self-supervised learning, or anomaly / out-of-distribution detection is appreciated but not required. A good level of English and an interest in both theoretical analysis and rigorous experimentation are strongly recommended.
Applications should include a detailed CV, a cover letter, academic transcripts from the Master’s or engineering’s years, and contact details of one or two references.

Formation et compétences requises :

Adresse d’emploi :
Rouen Normandie

Document attaché : 202607301050_PhD_LITIS.pdf