Internship – Observatory briefing paper analysis on disease outbreak sources, DIAD – WOAH HQ
Paris, France
| Context |
| The World Organisation for Animal Health is a leading intergovernmental organisation representing 183 Members worldwide. Through its activities, WOAH makes a decisive contribution to improving animal health, protecting animal welfare and strengthening Veterinary Services. The Organisation provides transparent information on world’s animal health situation, and promotes international standards, particularly in terms of the safety of trade in live animals and animal products. More information can be found on WOAH’s website. Joining WOAH means taking part in the development of one of the leading international organisations, recognised and associated with other multilateral institutions, in the field of worldwide health. It means helping to build a global approach to health, combining animal and human health in a “One Health” approach. It means joining teams motivated by the impact of their actions, the sense of their collective commitment and their recognised professionalism in their respective fields of expertise.WOAH’s headquarters are based in Paris. The Organisation is present on every continent through 13 Regional or Sub-regional Representations. WOAH has 250 staff members, two-thirds of whom are based at headquarters. The mission of the Data Integration and Analytics Department (DIAD) is to enhance WOAH’s decision-making capacities by analysing data from diverse internal and external sources and providing evidence-based insights for WOAH, its Members and partners. Through advanced analytics, data integration and knowledge generation, DIAD supports data-driven decision-making across the Organisation. Within DIAD, the WOAH Observatory monitors the implementation of WOAH international standards by its Members, through a set of monitoring indicators presented in its reports, including the most recently published ‘ Implementation of WOAH Standards: the Second Observatory Monitoring Report’. The Observatory also analyses how WOAH standards perform in real-world conditions. The information reported by Members to the World Animal Health Information System (WAHIS) on the sources and pathways of outbreaks of WOAH-listed diseases, complemented by scientific literature and expert experience, could strengthen the evidence base used in standard-setting, but it is not yet consolidated into a structured analytical framework. In this context, DIAD is offering an internship opportunity within the Observatory team for a motivated student interested in veterinary epidemiology and data science. Based at WOAH Headquarters in Paris, the intern will contribute to an Observatory briefing paper on the sources of disease outbreaks. |
| Job Description |
| Positioning and reportingThe intern will join the Observatory team of the Data Integration and Analytics Department (DIAD), under the authority of the Head of DIAD and the direct supervision of the Senior Scientific Officer of the Observatory. The intern will work in collaboration with the Epidemic Intelligence team (EPIQ) of DIAD and the World Animal Health Information Department (WAHID), and will have the opportunity to interact with the WOAH Standards Department, the Terrestrial Animal Health Standards Commission (TAHSC) and external experts, such as representatives of Veterinary Authorities and former Chief Veterinary Officers. |
| Job purposeThe purpose of this internship is to collate and analyse real-world evidence on the sources and pathways of outbreaks of WOAH-listed diseases, to support the TAHSC in prioritising and refining WOAH standards. The project will combine quantitative aggregation of WAHIS data, qualitative analysis supported by large language models (LLMs) to standardise and interpret reported outbreak sources, and triangulation with scientific literature and targeted interviews. The intern will contribute to an Observatory briefing paper and to an assessment of the feasibility of developing related Observatory monitoring indicators. |
| Missions and activities1. Selection of diseases and regionsCarry out a preliminary assessment of WAHIS immediate notifications.Propose a selection of diseases and regions for the analysis. 2. Data extraction from WAHIS Immediate Notification and Follow-Up Reports (INFUR)Develop a reproducible pipeline (R or Python) to extract data from WAHIS immediate notifications and follow-up reports, including their free-text fields.Automate the download and processing of the related PDF documents. 3. Quantitative aggregation and LLM-supported qualitative analysisAggregate and describe the reported sources and pathways of outbreaks by disease, species, region and over time.Use LLMs to categorise the reported outbreak sources andassessAssess the quality of the LLM-supported classification (e.g. manually reviewed validation sample, agreement metrics) and document its limitations. 4. Triangulation with scientific literature and targeted interviewsConduct a targeted review of the scientific literature on the sources and pathways of outbreaks of the selected diseases.Prepare and conduct targeted interviews with experts, such as representatives of Veterinary Authorities and former Chief Veterinary Officers, to provide contexts, the classification of sources and observed patterns. 5. Reporting and feasibility assessmentContribute to the drafting of the Observatory briefing paper.Assess the feasibility of developing related Observatory monitoring indicators.Document the data, methods and results. The Head of DIAD may, when necessary, assign to the incumbent any other duties, responsibilities and activities within the intern’s area of competence. |
| Requirements |
| Qualifications and ExperienceRequired qualifications and experience– Education: currently enrolled in a Master’s degree (M1/M2) in veterinary epidemiology, epidemiology, public health, animal scienceveterinary medicine, data science or a related field with a strong quantitative component.– Experience: academic or practical experience (projects, previous internship) in epidemiological data analysis with R or Python. Additional experience (asset)– Experience with natural language processing or LLM-based applications for text analysis.– Experience in conducting literature reviews or qualitative interviews.– Knowledge of WAHIS, WOAH international standards or animal disease surveillance and reporting. Expected SkillsTechnical skills– Strong data science programming skills in R or Python, including automated retrieval and processing of documents (e.g. PDF files).– Sound knowledge of veterinary epidemiology, including outbreak investigation and disease transmission pathways.– Ability to combine quantitative and qualitative analysis, including the use of LLMs to analyse free-text data.– Good practices in reproducible code: version control (Git), documentation, testing.– Excellent command of English (written and spoken); knowledge of French or Spanish is an asset. Personal and Interpersonal skills– Analytical mind, rigour and attention to data quality.– Autonomy, curiosity and ability to learn new tools quickly.– Critical approach to AI outputs and ability to synthesise information from multiple sources.– Ability to work in a multicultural and multidisciplinary team and to communicate with internal and external stakeholders. |
| Additional Information |
| Working conditionsThe post is a full-time internship position based at the WOAH Headquarters in Paris. It requires long hours in a seated position at a computer. – Salary: 715€ / month.– Duration: six (6) months.– Start date: as soon as possible.– Location: WOAH Headquarters, 12 rue de Prony, 75017 Paris, France. EligibilityThis internship requires an agreement with the student’s academic institution. |
| General InformationWOAH places high value on a multicultural and positive work environment. WOAH is an equal opportunity employer and welcomes all qualified candidates, irrespective of their origin, gender, opinions or beliefs. If you are interested in this internship, please complete your application online at the latest by 30 November 2026. All applications will be reviewed after the closing date of the publication. |
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