Informations générales
Intitulé de l'offre : Post-doctoral researcher in natural language processing M/F (H/F)
Référence : UMR7118-SABMAR-022
Nombre de Postes : 1
Lieu de travail : NANCY
Date de publication : mardi 1 avril 2025
Type de contrat : Chercheur en contrat CDD
Durée du contrat : 12 mois
Date d'embauche prévue : 1 septembre 2025
Quotité de travail : Complet
Rémunération : Between €3,000 and €4,200 gross monthly depending on experience
Niveau d'études souhaité : Doctorat
Expérience souhaitée : 1 à 4 années
Section(s) CN : 01 - Interactions, particules, noyaux du laboratoire au cosmos
Missions
The post-doc recruited will develop research to explore to what extent and how multiword expressions and their linguistic features are encoded in large language models.
Activités
The term « multiword expression » (MWE) refers to a combination of multiple lexical items that displays irregular composition possibly on different linguistic levels (morphology, syntax, semantics, …). They include a large variety of phenomena such as idioms (run around in circles), support verb constructions (take a walk), nominal compounds (dry run), complex function units (in spite of). They have been the subject of extensive research work in the NLP community over the last 50 years.
The goal of this post-doc position is to investigate to what extent large language models encode multiword expressions and their various levels of idiomaticity and fixedness. In particular, the hired post-doc will develop methods to extract linguistic features about multiword expressions in context from large language models.
The methods will be experimented on French and will be used to provide aids for French L2 learners when reading MWE occurrences in authentic texts.
Compétences
The hired post-doc researcher should have the following skills:
* expertise in deep learning for NLP and notably large language models
* excellent programming skills
* Good linguistic skills
* good knowledge of French would be a plus
* team spirit
Contexte de travail
The position is part of the STAR-FLE project (STrategic Adaptations for better Reading and Text Comprehension in FFL, https://www.starfle.fr/en, 2024-2027) funded by the French National Research Agency (ANR). The project aims to propose innovative digital solutions in the area of Natural Language Processing (NLP) that may improve text comprehension for French L2 learners and assist teachers in managing multiple levels of learners. In particular, it will propose context-based aids for understanding lexical issues as well as MWEs found in authentic texts. The hired researcher will be fully integrated in the project team.
Contraintes et risques
Applicants should hold a PhD thesis n natural language processing, in computational linguistics, in computer science, or in applied mathematics
Informations complémentaires
The applicants should submit a coverage letter, a CV including their publications, a list of references for recommandation, on the following official web site: emploi.cnrs.fr