QCBS Intensive course in biodiversity science

Offered each year and organized at one of the affiliated university’s research station, this course brings together the expertise from our researchers to offer a unique training experience. 

Summer school in biodiversity modelling

This annual summer school will give you the opportunity to further your knowledge of biodiversity modelling, in an informal and friendly atmosphere. The 2024 edition will be on the theme: Indicators to monitor biodiversity changes.

The Kunming-Montreal Global Biodiversity Framework adopted in December 2022 sets ambitious objectives to protect and restore biodiversity for 2030. Parties to the Convention on Biological Diversity are currently developing their plan to meet these objectives in preparation for the next COP that will be held in the fall 2024. A critical aspect of this work will be the elaboration of a set of indicators to monitor the achievement of the GBF, from local to global scales.

The main objective of the 2024 summer school in computational biodiversity science will be to develop a report of the current state of biodiversity for Canada, based on the most recent science on biodiversity indicators and using state-of-the-art technologies in data science. The intensive course consists of a five-day workshop dedicated to data analysis, complemented by short technical lectures by leading scientists in the domain.

Summer School in Advanced Statistics for the Life Sciences

This annual summer school will provide the opportunity to deepen your knowledge in advanced statistics, in a convivial environment.

The main theme of this summer school is “Hierarchical Models in the life sciences”. The course aims to introduce hierarchical models from both a theoretical and practical point of view. Hierarchical models with and without constraints (e.g. spatial and/or time) as well as multivariate hierarchical models will be presented. Everything will be done using R with an introduction to Stan. Bring your dataset!

Path Analysis in Ecology

Offered every year by Bill Shipley, one of the world experts on path analysis from Université de Sherbrooke.

This course is for both Master’s and PhD students.

Ecologists often pose cause-and-effect hypotheses involving several variables in systems for which controlled randomised experiments are not possible. When this occurs one must use a set of statistical methods called “structural equations modelling” or “path analysis”. In this intensive five-day course you will learn the basics of these methods and how to apply them in your ecological research. Theoretical sessions will be interspersed with practical sessions using the free R software. You are encouraged to use your own data sets whenever possible.