Job offer

European Commission; France; Sur place; EUR 35 000 - 45 000; Plein temps

Résumé du poste

A leading research organization seeks a postdoctoral researcher in natural language processing. The candidate will develop machine learning techniques for information extraction from medical research articles. This position supports the FAIRClinical project, aiming to enhance data interoperability and reusability.

Qualifications

• PhD holder in relevant fields essential.
• Skills in machine learning and natural language processing required.
• Good command of English required.

Responsabilités

• Identify data sources for extraction and normalization.
• Develop text mining pipelines for extraction.
• Evaluate text mining methods and participate in publications.

Connaissances

Supervised machine learning

Semi-supervised machine learning

Natural language processing

Deep learning

Formation

PhD in computer science or computational linguistics

Description du poste

Organisation/Company CNRS Department Laboratoire Interdisciplinaire des Sciences du Numérique Research Field Engineering Computer science Mathematics Researcher Profile Recognised Researcher (R2) Country France Application Deadline 1 Aug 2025 - 00:00 (UTC) Type of Contract Temporary Job Status Full-time Hours Per Week 35 Offer Starting Date 1 Sep 2025 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No

Offer Description

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.

- 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.

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.

- 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