The World Organisation for Animal Health (WOAH) is an intergovernmental organisation of 183 Members working to improve animal health, animal welfare and Veterinary Services worldwide. Within its Data Integration and Analytics Department (DIAD), the WOAH Observatory monitors the implementation of WOAH international standards by Members through a set of monitoring indicators. The Observatory tracks World Trade Organization (WTO) data, such as Sanitary and Phytosanitary (SPS) notifications and specific trade concerns (STCs) available on the ePing platform. These documents are largely free text and their links to the chapters of the WOAH Codes and Manuals are not yet systematically established, while current indicators are primarily descriptive and lack measures of statistical uncertainty.
The intern will join the Observatory team under the Head of DIAD, supervised by the Senior Scientific Officer of the Observatory, with functional supervision by a DIAD Data Scientist. The purpose of the internship is to map SPS notifications and STCs submitted by WOAH Members to the chapters of the WOAH Codes and Manuals, quantify the relevance of each chapter to national regulations in the context of trade, and strengthen the statistical basis of the Observatory's indicator matrix.
Key activities:
- Develop a reproducible data pipeline (R or Python) to collect SPS notifications and STCs from ePing, integrating LLMs to map them against the relevant chapters of the WOAH Terrestrial and Aquatic Codes and Manuals; document and present the work.
- Triangulate pipeline outputs with other sources (e.g. national regulations), assess the quality of automated extraction (validation samples, accuracy metrics), and quantify the relevance of each chapter to national regulations in the context of trade.
- Contribute to scoping the Observatory's thematic study on trade, interacting with the WOAH Standards Department and the WTO SPS Secretariat.
- Perform basic statistics for the Observatory's indicator matrix, review indicator definitions, and propose approaches to quantify uncertainty (e.g. confidence intervals).
Requirements: currently enrolled in a Master's degree (M1/M2) or final year of an engineering school in data science, statistics, computer science, epidemiology, economics or a related quantitative field; academic or practical experience in data processing and statistical analysis with R or Python; strong programming skills; knowledge of NLP/text extraction and LLMs; sound knowledge of statistics including uncertainty quantification; good reproducible-code practices (Git, documentation, testing); excellent English (French or Spanish an asset). Assets: NLP/LLM experience, knowledge of international trade and the WTO SPS Agreement, interest in animal health, public health or One Health.
Conditions: full-time, six-month internship at WOAH Headquarters in Paris, with a monthly allowance of €715.
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 WOAH application form (https://app.smartsheet.com/b/form/01a144efe4337c37bdb99da33a87dd7c) by 4 November 2026. The internship requires an agreement with the student's academic institution, and the selected candidate must be able to start in person in Paris no later than 4 January 2027.