Teaching

Our interaction with master and PhD students tells whether we are able to convey our knowledge in scientific computing to non-professionals. This is quite a challenge, as many of our students never had any course even remotely similar to what we teach them. Thanks to a yearlong struggle from our side, we now have a quite stable set of exercises that we use in our classes.

We generally start with a course on scientific computing in R. This course takes several days, and should make the students acquainted to programming in R. Our free lecture material can be found here. Accessory material can be found here.

Those that follow our environmental modelling classes are then gently introduced in the fine art of mathematical modelling. You can see a selection of the type of problems our students solve during these classes in a number of shiny applications on this page. Change the values of parameters (sliders) and look at the effect on the model outcome.

  • The chemostat is the first model that students implement in R. It describes how algae grow in a flow-through system.
  • A more realistic biological model that represents a simple ecosystem for a marine bay is the NPZD application.
  • The nitrification example is a biogeochemical model representing the eutrophication of the Westerschelde, and its impacts on the oxygen concentrations.
  • Finally, there is a fish management example where the students calculate the consequences of plans for fisheries in a lake over the next 50 years. This is a quite sophisticated shiny application that allows you to keep certain model runs and compare it with the reference run.