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2016-03-17

LABEF

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Our goal

Le Laboratoire de Biomathématiques et d’Estimations Forestières (LABEF) aims at analyzing the applicability of mathematics tools in life sciences and at understanding the interactions between ecological processes, anthropogenic factors and structure of terrestrial ecosystems, with a clear link to management and policy.

Prof Romain Glèlè Kakaï

Recent Posts

The coordination of the Master Programme in Statistics major Biostatistics of the Doctoral School of Agronomic and Water Sciences (ED-SAE) of the University of Abomey-Calavi (UAC) is pleased to launch the call for application for the admission and selection of the 11th batch of students for the academic year 2023-2024.
Collaboration between the German-West African Centre for Global Health and Pandemic Prevention (G-WAC) and the Humboldt Research Hub HRH-SEMCA
On the COVID-19 pandemic and vaccines effectiveness in West Africa
Artificial Intelligence and Precision Agriculture
AGNES-BAYER Science Foundation Research Grant for Biodiversity Conservation & Sustainable Agriculture in Sub-Saharan Africa
DAAD In-country(In-region Scholarship Programme for Subsaharan Africa.
DAAD “In-Country/In-Region Scholarship Programme” for Sub-Saharan Africa at University of Abomey-Calavi
“In-Country/In-Region Scholarship Programme” for Sub-Saharan Africa at University of Abomey-Calavi, Doctoral school of agronomic and water sciences in Benin – Strengthening Higher Education and Research in West and Central Africa
Selected applicants for master in Biostatistics (on a fee-paying basis)
TEBWA scholarships programme : List of grantees
Call for applications for scholarships for Master degrees in Biostatistics and Epidemiology at the University of Abomey-Calavi, Benin
DAAD In Country/In Region Scholarship Programme
Call for applications for the 9th batch of students in Biostatistics for academic year 2021-2022
AGNES-BAYER Science Foundation Research Grant for Biodiversity Conservation & Sustainable Agriculture in Sub-Saharan Africa
Introduction to infectious diseases and data modelling (2nd edition)

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