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Ecologist expert in microbial interaction networks F/M

Vacancy details


Future organization (department / unit)

CIRAD, the French Agricultural Research Centre for International Development, works with its partners in southern countries to generate and pass on new knowledge to support agricultural development and innovation.

It has one main objective: to build sustainable farming systems for tropical and Mediterranean regions capable of feeding ten billion human beings by 2050 while preserving the environment.  



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Position description


Science - Ecological sciences



Job title

Ecologist expert in microbial interaction networks F/M

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Job description

The researcher will develop and use cutting-edge interaction network analysis tools to unravel ecological associations among microbial communities. The medium-term objective of these studies is to better understand how microbiota affects the health of the host plant.
The plant microbiota—a complex and tightly-knitted community of microorganisms—dynamically responds to biotic and abiotic environmental disturbances. Hence, interactions among members of the plant microbiota (competition, commensalism, amensalism and mutualism) form a continuously evolving network. We hypothesise that biotic and abiotic stress-mediated modulations of the microbial interaction network affect the health of the host plant (growth, development, disease occurrence, etc.).
The researcher—with a PhD in biostatistics or bioinformatics applied to the analysis of ecological networks and with skills in microbial ecology/microbial metagenomics—will develop microbial ecology research projects focusing on the networks of microbial interactions within agro-systems. Using mathematical and statistical modelling, the researcher will study dynamic co-occurrence networks covering different plant microbiota members (viruses, bacteria, fungi and other microeukaryotes), or the different genomic components of multipartite viruses. Specifically, the researcher will seek to adapt graph construction and statistical analysis algorithms to the particularities of massive metagenomic sequencing data. The researcher will also carry out a functional description of node interactions (e.g.; antagonism or synergy) and will aim at associating massive metagenomic sequencing data matrices with environmental co-variables.
The researcher will work in close collaboration with biologists from the PhytobioM and ViroM departments of the PHIM research unit. Several viral and microbial models studied in these two departments will benefit directly from a network approach. These teams address ecological and evolutionary issues at different scales ranging from genomics of multipartite viruses at the plant level to the study of viral and microbial communities at the landscape level and the factors that determine their structure and composition.
The identification of environmental factors or bioindicators would be an essential output in providing assistance in the management and piloting of agrosystems, and an asset for MetaHealth, an expertise structure hosted by PHIM.

Desired profiled

- Strong skills in analysis and inference of interaction networks
- A solid scientific base in ecology and community evolution, especially microbial communities
- Skills in mathematics, bioinformatics, biostatistics and use of several programming languages (R, Python, etc.)
- Good oral and written English practice
- Ability to work in a team and share your expertise
- Ability and enthusiasm for working in collaboration with teams from different disciplines and for research with developing countries.

Position constraints

Work on screen longer than 4 hours

Socio-professional category


Salaire base France, hors indemnités d'expatriation le cas échéant

27-37 K€


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