A 24-month postdoctoral position is available at INRAE Jouy-en-Josas, France, focusing on the epidemiogenetics of resistance to coccidiosis in chickens. The role is part of the European Partnership Animal Health Welfare (EUPAHW) and involves analyzing experimental data, developing simulation models, and disseminating results through scientific articles and conferences. The successful candidate will join the GeMS team within the Animal Genetics Integrative Biology (GABI) unit. Applicants should hold a PhD in animal genetics, epidemiology, biostatistics, or computational biology, with proficiency in statistical programming and knowledge of epidemiological modeling or quantitative genetics. The gross monthly remuneration ranges from 3205 to 3641 Euros, depending on experience. The application deadline is October 31, 2026, with a start date of January 1, 2027.
| Department | Animal Genetics Integrative Biology (GABI) |
| Position Type | Postdoctoral Position |
| Discipline | Animal Genetics, Epidemiology, Biostatistics, Computational Biology |
| Research Area | Epidemiogenetics of Resistance to Coccidiosis in Chicken |
| Degree Required | PhD |
| Experience | Experience in infectious disease modelling and/or quantitative genetics is appreciated. |
| Salary | Between 3205 and 3641 gross per month depending on professional experience |
| Funding | European partnership EUPAHW (European Partnership Animal Health Welfare) |
| Contract Duration | 24 months |
| Deadline | 2026-10-31 |
| Required Documents | CV, motivation letter |
| Employer Address | INRAE, Ile-de-France Jouy-en-Josas Antony, 78350 near Paris |
| Employer Contact | ITHURBIDE Marie ([email protected]), ESTELLE-FABRELLAS Jordi ([email protected]) |
The postdoctoral project focuses on the epidemiogenetics of resistance to coccidiosis in chickens, aiming to improve resistance to infectious diseases in livestock. It will utilize data from the EPIDGENCO experiment, which involved two contrasting chicken lines (Fayoumi and commercial broiler) monitored for coccidiosis infection. The project involves three main areas: analyzing experimental data to estimate and compare epidemiological and production parameters between breeds using SIR-type infection dynamics models; modeling and simulation to define plausible genetic parameters for five studied traits and simulate coccidiosis epidemics in virtual farms; and disseminating findings through scientific articles and conferences. The goal is to guide genetic selection for traits that promote animal health at both individual and group levels.
This position is suitable for researchers with a PhD in animal genetics, epidemiology, biostatistics, or computational biology. Candidates should have strong skills in statistical programming (R and/or Python), experience with complex datasets, and knowledge of epidemiological modeling or quantitative genetics. Experience in infectious disease modeling is particularly valued. The role requires rigor, organization, and the ability to work independently.
INRAE is the French National Research Institute for Agriculture, Food, and Environment. It is a major player in the research and innovation community, with 12,000 people across 272 research and experimental units in 18 regional centers throughout France. Internationally, INRAE is among the top research organizations in agricultural, food, plant, animal, ecology, and environmental sciences. Its goal is to be a key player in transitions necessary to address global challenges such as a growing world population, climate change, resource scarcity, and declining biodiversity.
The postdoctoral position has a duration of 24 months.
Applicants must hold a PhD in animal genetics, epidemiology, biostatistics, computational biology, or a related discipline.
Applicants must send a CV and a motivation letter.
The contact persons are ITHURBIDE Marie ([email protected]) and ESTELLE-FABRELLAS Jordi ([email protected]).
This listing is summarised from the official advertisement. Always confirm the details, including the closing date, on the employer's own site before applying.
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