Internship: Modeling Cattle Herds in Native-Tree Sylvopastoral Systems
Join INRAE for a 6-month research internship modeling sustainable beef cattle farming systems and climate resilience.
Best for:Best for Master 2 or engineering students in agronomy, animal science, or data science with strong R or Python and modeling skills.
Overview
The French National Research Institute for Agriculture, Food, and Environment (INRAE) invites applications for a 6-month research internship within the Herbivores joint research unit (UMRH) located in Saint-Genès-Champanelle, France. The successful candidate will work on the SyLvA-Herd project, focusing on the adaptation of a farm-scale mechanistic model (SEBIEN) to evaluate sylvopastoral practices involving native trees. Responsibilities include organizing commercial farm datasets, parameterizing relationships between tree canopy density and livestock performance, and conducting scenario analyses to optimize greenhouse gas mitigation and climate adaptation. The intern will collaborate closely with an interdisciplinary team of researchers and engineers in France and Brazil.
What you'll do
- Organize, clean, and document empirical plot, herd, and climate datasets from commercial farms.
- Construct variables and scenario classes reflecting tree-canopy density and functional tree diversity.
- Adapt and parameterize relationships linking sylvopastoral structure to forage production, nutritional value, and animal performance using R or Python.
- Integrate and run algorithms within the SEBIEN farm-scale modeling framework to simulate greenhouse gas emissions and feed balance.
- Perform model evaluation by comparing observed and simulated values through graphical inspections and error metrics such as RMSE and R-squared.
- Conduct global sensitivity analyses to determine the parameters that most significantly influence model outputs.
- Simulate no-tree baseline configurations alongside various sylvopastoral management and climate scenarios to identify optimal trade-offs.
Requirements
Degree required: Enrolled in Master's year 2 or engineering degree in data science, statistics, agronomy, or animal science
Language: Fluency in spoken English
Instruction: English / French
- Experience with mechanistic modeling frameworks
- Proficiency in R or Python software for data preparation and analysis
- Strong background in agronomy, animal science, or data science
- Must be enrolled in a qualifying Master 2 or engineering curriculum
Funding & terms
How to apply
Deadline: 2026-10-15
Interested applicants should submit their Curriculum Vitae and a motivation letter via email directly to the provided contact addresses.
- CV
- Cover letter
Contact
Luciano Barreto-Mendes· Researcher
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