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Traditional foods for the future: transdisciplinary approaches to advance Sustainable Development Goals
2-14 February 2025
This on site course in Zambia aims to provide skills and methods for developing transdisciplinary research to promote advancement of Sustainable development Goals in Low and Middle Income countries by mobilizing local traditional foods. Participants will experience how this requires both in-depth expertise and knowledge from various disciplines as well as synthesis of disciplines and rooting with local stakeholders.
Statistics for Data Science
10 - 14 February, 2025
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. Moreover, the course will give you insights in the connections between modern modeling strategies and will teach you to ask the right questions in order to choose the best method for the data at hand. Illustrations will come from relevant case studies.
Essentials of Modelling: How to set up a good modeling practice
17- 21 February 2025
This course is intended for everyone who is working on a modelling project and wants to learn more about mathematical and computational modelling.
Remote Sensing for Environmental Sciences
17 - 21 February 2025
This course offers the basic theories in the field of remote sensing, starting from the information needs of various land applications. Hands-on skills for handling remote sensing data are central in the practical exercises.
Root Ecology
23 - 28 February 2025
This postgraduate course focuses on root ecology, and how roots grow, function and interact with the surrounding environment. We will discuss differences and similarities between roots in natural ecosystems and roots of agricultural plants.
Tidy data transformation and visualization with R (online) - March 2025
4, 7, 11 and 14 March 2025
In this workshop, participants will learn the principle of tidy data, how to transform and combine datasets using the tools from the tidyverse and how to generate advanced visualization with the ggplot2 package.
The Science of Conservation
7-18 March 2025
The science of conservation is an interdisciplinary field that focuses on the study and application of principles, methods, and practices aimed at strategies to preserve natural resources, biodiversity and ecosystems. This course addresses the principles of sustainable conservation and conservation strategies where we will focus on rewilding.
Seed systems and opportunity crops: diversifying food systems through resilient seed systems
23 March to 3 April 2025
This course is the follow-up of and will build on the 2023 Participatory Plant Breeding and Resilient Seed Systems postgraduate course that also focused on smallholder engagement in plant breeding and seed system development.
Multivariate Analysis
25, 26, 27, 31 March and 1 April 2025
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.
Microbial Ecology 6 -11 April 2025
6 - 11 April 2025
Microbial communities are vital to life on Earth. These “invisible creatures” catalyze global elemental cycles, regulate climate, and support human and environmental health and thereby play a critical role in mitigating climate change, ensuring sustainable food and energy production as well as sustainable industrial production. This one-week course explores the dynamic interplay between microbiomes and their environments, focusing on their contributions to sustainability.
Boundary line analysis for yield analysis
23 and 24 April 2025
This is a two-day course that covers the theory and practical application of the boundary line methodology proposed by Webb (1972).
Basic Statistics
14, 15, 16, 21 and 21 May 2025
This is a refresher course aimed at PhD candidates. The level is that of a second course in Statistics. We will refresh basic knowledge of Probability, Statistical Inference (Estimation with confidence intervals and Testing), t-tests, standard cases of the Linear Model: Regression, ANOVA and ANCOVA. For our analyses we use software written in R. Programs will be provided. Other topics: Experimental Design, Non-parametric Tests, and Chi-square Tests. Some time is reserved to discuss statistical problems of the participants.
Mixed Linear Models
10, 11 and 12 June 2025
In this module we discuss how to analyse data for which the assumption of independence is violated. So: Do you have a nested experimental set-up? Or repeated measurements? Or weight of the same animal over time? Or pseudo-replication? Then, you are likely to need Mixed Models. In this course, you will learn all about it!
Generalized Linear Models
18, 19 and 20 June 2025
In this module we study how to analyse data that are not normally distributed. We look at fractions (logistic regression), counts (Poisson regression, log-linear models), ordinal data (threshold models), and overdispersion. We discuss (quasi-) maximum likelihood estimation and the deviance.
Resilience of living systems
23 - 27 June 2025
Resilience is the capacity of a system to maintain or recover certain functions while undergoing shocks and stresses. It emerges from the many interactions between people and natural and/or artificial system components, and the capacity of people to adapt. During this course, the participants become acquainted with different resilience concepts and their application from an interdisciplinary perspective. Accordingly, we will address how resilience theory can be used to tackle fundamental and societal issues from a socio-economic and bio-physical perspective and will provide a critical reflection on the relevance, use, and applicability of the concept of resilience. The objective of this course is thus to connect resilience concepts to viable applications by offering an efficacious analytical/computational approach.
Bayesian Statistics
1 - 4 July 2025
Classical statistics offers a powerful toolbox for data analysis. This toolbox, however, may not always be sufficiently flexible for modern data situations. The Bayesian framework allows for the integration and inclusion of information from many sources as well as a natural quantification of uncertainty in subsequent analysis.
Soil Biology Lab Skills Course For Assessing Soil Functions
1 - 5 September 2025
This course will provide the participants with an overview of a range of methods related to the five soil functions and will provide detailed practical training in a subset of measures. The training will be a combination of lectures, laboratory and field sessions (interactive lectures and practical sessions each day). Assessing a range of measurement types, from simple visual assessments in the field, to training in microscope identification techniques for nematodes and earthworms, and functional measures in the lab such as MicroResp. All methods described in the course will be made available to participants as well as advice on how to analyse the data.
The Art of Modelling
1 - 12 September 2025
Modelling is a crucial part of today's science. Among other things, models are used for assessing sensitivity of systems to disturbances or changes in external factors, and for predictions of future system states. This course provides an introduction to modelling with a focus on systems analysis using dynamic simulation models.