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INRAE

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PhD in Bayesian Spatiotemporal Modeling for Plant Epidemiology and Cassava Witches’ Broom Disease INRAE in France

Degree Level

PhD

Field of study

Epidemiology

Funding

Funding details are not specified in the post. This is a PhD opportunity hosted at BioSP, INRAE, Avignon, with supervision from CIRAD and INRAE researchers.

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Country

France

University

INRAE

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Keywords

Epidemiology
Environmental Science
Agriculture
Biology
Salud Pública
Bayesian Statistics
Food Insecurity
Statistics

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About this position

PhD opportunity in novel statistical approaches for integrated multi-source and multi-scale data analysis in plant epidemiology, with application to Cassava Witches’ Broom Disease (CWBD).

The project addresses how climate change and globalization are accelerating crop disease emergence and threatening food security. The PhD will develop Bayesian spatiotemporal models to integrate heterogeneous data sources, including environmental, agricultural, spatial, and societal data, for epidemic risk assessment and optimized surveillance strategies.

Research themes: spatiotemporal modeling, Bayesian statistics, epidemiology, multi-scale data integration, surveillance design, plant health, food security.

Project context: CWBD is a critical threat to cassava production in French Guiana and Brazil, with methods intended to have broader relevance for plant, animal, and human epidemiology. The work includes collaboration with field stakeholders such as FREDON Guyane to build decision-support tools for disease management.

Supervision: Mathilde Chen (CIRAD), Marie Denis (CIRAD), and Samuel Soubeyrand (INRAE). The project is hosted at BioSP, INRAE, Avignon.

Eligibility highlights: strong interest in quantitative epidemiology and statistical modeling; ability to work with complex multi-source datasets; collaborative mindset for applied research with stakeholders.

Timing: start date is late 2026 / early 2027. No deadline or funding details are specified in the post.

Funding details

Funding details are not specified in the post. This is a PhD opportunity hosted at BioSP, INRAE, Avignon, with supervision from CIRAD and INRAE researchers.

What's required

Applicants should be interested in Bayesian spatiotemporal modeling, multi-source and multi-scale data integration, and epidemiological analysis. The project emphasizes quantitative skills and the ability to work with environmental, agricultural, spatial, and societal data. Collaboration with field stakeholders is part of the work.

How to apply

Contact the listed supervisors by email to express interest and ask about the application process. Reach out to Marie Denis, Mathilde Chen, and Samuel Soubeyrand with a brief introduction and relevant background. No formal application portal is provided in the post.

More information can be found here

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