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Agricultural and Environmental Sciences● OpenInternshipPreview

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.

INRAE · Saint-Genès-Champanelle, France · R1 · First-stage researcher
More professors at INRAE
sylvopastoral systemsmechanistic modelinggreenhouse gas emissionslivestock productionclimate resilienceagroecology
This is a internship position — not a PhD studentship.
Deadline
—
Funding
Stipend
€4.5/hr
Start date
2027-01-01
Temporary
Location
Saint-Genès-Champanelle
France

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.

internshipcattlemodelingSEBIENagronomyanimal scienceRPython

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

Required skills
  • 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
Nice to have
Knowledge of temperate and tropical livestock systemsFamiliarity with sylvopastoral systems and tree-pasture interactionsUnderstanding of greenhouse gas emissions in agricultural contextsExperience executing global sensitivity analyses or climate scenarios
Eligibility
  • Must be enrolled in a qualifying Master 2 or engineering curriculum

Funding & terms

Type
Stipend
Amount
€4.5/hr
Duration
6 months
Programme
SyLvA-Herd
INRAE

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.

Documents required
  • CV
  • Cover letter
✉Apply by email

Contact

LB
Prof.
Luciano Barreto-Mendes
Herbivores Joint Research Unit (UMRH)
Lab
Livestock Systems, Agroecological Transition, Resilience and Product Quality team (STARQ)
INRAE
SyLvA-HerdFrance
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