Courses open for registration

In many PhD research studies the use of geodata has become essential. We offer PhD students the opportunity to join this course to understand and practice basic geo-information concepts. The course is a 6 ECT course for MSc students, consisting of 4 clusters (see annex 1). PhD candidates may select which clusters to follow. Each cluster is 1.5 ECT, 40 hours in 2 weeks. PhD candidates can work on their own geodata related questions during the course.

During the Image analysis course, the foundation was laid for classical and modern computer vision techniques. During this continuation course we will go deeper into two image analysis techniques which are relevant for animal scientists: tracking and pose estimation.

This post-graduate course on Theoretical Ecology will focus on bifurcations in dynamical systems and participants will learn quantitative approaches to assess qualitative changes in biological systems that occur when conditions change.

This course will address the management of data in a Findable, Accessible, Interoperable and Reusable way. Participants will be introduced to the why and how of FAIR data and create new FAIR datasets or raise the FAIRness of existing datasets, employing state-of-the-art tools.

The aim of this course is to provide an introduction to R and R Studio. It introduces the participants to R language syntax, to enable them to write their own R code. They will also learn about R data-types and data-structures, and they will be taught how to explore the data and produce plots. The course will be a combination of lectures and practicals.

The purpose of this course is to familiarize participants with statistical methods to analyse uncertainty propagation in spatial modelling, such that they can apply these methods to their own models and data. Both attribute and positional errors are considered. Attention is also given to the effects of spatial auto- and cross-correlations on the results of an uncertainty propagation analysis. Computer practicals make use of the R language for statistical computing.

The aim of this course is to provide an introduction to R and R Studio. It introduces the participants to R language syntax, to enable them to write their own R code. They will also learn about R data-types and data-structures, and they will be taught how to explore the data and produce plots. The course will be a combination of lectures and practicals.

This course will make you familiar with a modern toolbox of analysis techniques at the interface of statistics and machine learning. You will develop the skills to build and evaluate modeling strategies for complex (big, high-dimensional, hierarchically-structured) data as occurring in the areas relevant to WIAS and PE&RC.

The design and analysis of experiments, using plants, animals, or humans, are an important part of the scientific process. Proper design of an experiment, apart from its proper analysis and interpretation, is important to convince a researcher that your results are valid and that your conclusions are meaningful.

While much of statistics focusses on associations between variables and making predictions, the aim of structural equation modelling is to establish causal relationships between variables. The focus will be on classical structural equation models with a small number of (latent) variables, but we will also give an introduction to recent developments on methodology for high-dimensional data.

In this course, the participant will be provided with both the basic understanding of the principles of multivariate methods and the skills needed to use those methods in his/her own work. The course consists of lectures and computer practicals using RStudio.

Centered on the Bergville/Mont-aux-Sources/Royal Natal National Park area, the course aims to investigate past and current dynamics of the region and predict possible futures in an inter- / trans-disciplinary context.

Aquatic ecosystems play a crucial role in human health and well-being. Aquatic systems also provide diverse habitats, support high levels of biodiversity and vital ecosystems services. With over half of the human population currently living in cities, the health of urban waters is becoming ever more vital. Urban aquatic ecosystems, however, are under severe anthropogenic pressure. Unprecedented rates of global change add a sense of urgency to study the impacts of anthropogenic pressures, and to develop ways to restore and improve the robustness of urban aquatic ecosystems against these pressures.

In this two day workshop you will learn about two most common long read sequencing technologies: Pacific Bioscience an Oxford Nanopore Technology. You will learn how to work with the data, perform assembly, mapping, and compare the results of both technologies.