Informations générales
Intitulé de l'offre : Post-doctoral position in NLP in CHIST-ERA FAIRClinical project (M/F) (H/F)
Référence : UMR9015-NONNAD-004
Nombre de Postes : 1
Lieu de travail : GIF SUR YVETTE
Date de publication : lundi 12 mai 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 : monthly gross salary: between €3081.33 and €3519.85 (depends on the candidate's experience)
Niveau d'études souhaité : Doctorat
Expérience souhaitée : 1 à 4 années
Section(s) CN : 07 - Sciences de l'information : traitements, systèmes intégrés matériel-logiciel, robots, commandes, images, contenus, interactions, signaux et langues
Missions
The postdoctoral position is in the field of natural language processing and the researcher will join the European FAIRClinical project funded by CHIST-ERA. The postdoctoral researcher will develop machine learning approaches for information extraction from medical and clinical research articles and their supplementary materials.
Activités
- To identify the data sources needed for the extraction and normalization of the entities.
- To develop text mining pipelines for the extraction and normalization from full texts and supplementary materials.
- To evaluate the text mining methods.
- To participate in the team's publication and communication activities.
Compétences
- PhD in computer science, computational linguistics or alike
- Skills in supervised and semi-supervised machine learning, including deep learning
- Experience with natural language processing
- Good command of English, both spoken and written
- Capacity to work independently and as a team member
- Ability to prioritize tasks and take initiative
Contexte de travail
This position is part of the FAIRClinical project funded by CHIST-ERA, in which the objective is to enhance the FAIR-ness of all supplementary data files and significantly improve the reuse of unstructured clinical case report forms (CRFs). Supplementary data are commonly attached to a scientific publication, either directly in biomedical libraries such as PubMed Central, or via generalist deposition platforms such as Zenodo. CRFs collect the patient data in clinical research studies and trials, and represent an information-rich subset of clinical research literature and unstructured clinical study supplementary data. This project proposes to specifically enrich the contents—and therefore the interoperability, findability and reusability—of all supplementary data by delivering more normalized contents.
Le poste se situe dans un secteur relevant de la protection du potentiel scientifique et technique (PPST), et nécessite donc, conformément à la réglementation, que votre arrivée soit autorisée par l'autorité compétente du MESR.
Contraintes et risques
Risks related to using a display screen.