Modelling Stability of Meta-Ecosystems along Land-Sea Continuum
Develop advanced spatial simulation models to study biodiversity and stability in connected river and coastal ecosystems.
Best for:Best for quantitative ecologists or modellers with strong computational skills and experience in ecological network dynamics.
Overview
INRAE Rennes seeks a researcher to develop a spatial meta-ecosystem model addressing the land-sea continuum as part of the RIV2SEA project. Based in the DECOD research unit and collaborating with national and international partners, the position focuses on simulating species-rich food webs, nutrient fluxes, and dispersal dynamics. The work will extend the EcologicalNetworksDynamics.jl platform to evaluate ecological restoration strategies and ecosystem resilience. The candidate is expected to conduct in-silico experiments, contribute to code documentation, and publish high-impact research.
What you'll do
- Develop a spatially explicit meta-ecosystem model integrating species-rich food webs, nutrient fluxes, and species dispersal along the land-sea gradient.
- Perform and analyze in-silico experiments to evaluate meta-ecosystem resistance and resilience under spatial pressures.
- Simulate the effectiveness of various ecological restoration scenarios, such as wetland restoration and barrier removal.
- Publish at least one research paper in a major ecological journal detailing the findings.
- Contribute two days per month to the maintenance and documentation of the modeling platform in collaboration with project team members.
Requirements
Degree required: PhD or equivalent qualification in ecology, environmental sciences, computational biology, or a related quantitative field
Language: English proficiency for scientific communication and collaboration
Instruction: English
Publications: At least one paper in a major ecological journal resulting from the project
- Strong background in community ecology, food web theory, or spatial ecology
- Proficiency in scientific programming and computational modeling
- Experience working with complex ecological datasets or simulation frameworks
- Demonstrated capability in scientific writing and publishing research
Funding & terms
How to apply
Interested applicants should follow the instructions provided on the listing page to submit their application documents.
- CV
Contact
Alain Danet· Supervisor
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