The World Organisation for Animal Health (WOAH, founded as OIE) is an intergovernmental organisation representing 183 Members worldwide, working to improve animal health, animal welfare and Veterinary Services. The Data Integration and Analytics Department (DIAD) supports evidence-based decision-making through data integration and advanced analytics. WOAH coordinates STAR-IDAZ, a large international research effort on animal health, including the collection of research needs expressed by Members, experts and partners. These needs are mostly gathered through free-text forms, which makes consolidation, analysis and publication labour-intensive.
DIAD, in collaboration with the Science Department, is offering a six-month, full-time internship at WOAH Headquarters in Paris for a motivated student interested in data science and AI applied to research data. The intern joins the Data Science Lab under the Head of DIAD, supervised by the Data Manager and the AI Scientist, and designs, develops and documents data science and AI pipelines that automate the management of research needs and the extraction, summarisation and publication of animal health research priorities.
Responsibilities:
- Data understanding and preparation: review the research needs database and collection channels; build reproducible Python/R pipelines to ingest, clean, standardise and de-duplicate records; propose a data model and controlled vocabularies.
- AI-supported text processing: develop NLP and LLM pipelines to classify research needs, extract entities (pathogen, disease, species, topic, stakeholder), detect duplicates, and cluster and summarise needs into consolidated priorities; design an evaluation approach with human-in-the-loop review.
- Publication of research priorities: automate reports, tables, dashboards or web-ready content; integrate with DIAD data platforms following WOAH IT security rules.
- Documentation and knowledge transfer: use AI-supported coding tools with good engineering practices, document pipelines, prompts and models, prepare a user guide and final report, and hand over tools to the teams.
Expected deliverables: documented reproducible ingestion/cleaning pipeline; AI/NLP pipelines with performance evaluation; an automated report or dashboard of consolidated research priorities; technical documentation, user guide and final internship report.
Requirements:
- Currently enrolled in a Master's (M1/M2) or final year of an engineering school in data science, computer science, statistics, AI or a related quantitative field.
- Academic or practical experience with Python and/or R for data processing and analysis, including text data.
- Strong programming skills, hands-on use of AI-supported coding tools, good knowledge of NLP and LLM APIs, and reproducible-code practices (Git, documentation, testing).
- Assets: NLP/text mining/LLM experience (prompt engineering, RAG, embeddings), interest in animal health or One Health, data visualisation tools (Quarto, Power BI, Streamlit/Shiny), SQL and data modelling.
- Excellent English; French or Spanish is an asset.
Conditions: internship agreement with the student's academic institution required; salary 715€/month; start as soon as possible and no later than 4 January 2027, in person in Paris.
If you are interested in this internship, please complete your application online at the latest by 4 November 2026.
HOW TO APPLY:
Complete the application online via the application form at https://app.smartsheet.com/b/form/01a11a8d3bf47ee89fd3396ff5b08777 by 4 November 2026. All applications will be reviewed after the closing date.