Teaching
Scientific writing in English for doctoral students
This two-day block course is aimed at early doctoral students within the first two years after starting their doctorate. It is an intensive course covering all central aspects of writing scientific papers in English to equip students with all necessary insights and skills to write their first scientific paper. The course is particularly tailored for doctoral students with a technical background, like engineering, or computer science. Topics covered are academic integrity, scientific writing, scientific English, giving and receiving feedback, information research, project and time management. The course is designed as an interactive writing laboratory, where students give each other feedback and support.
Machine Learning for the Sciences
Machine learning algorithms enjoy a large and increasing number of technological applications. They help us to extract relevant information from big datasets and transform the way we interact with machines. In the sciences, machine learning emerges as a more and more routinely used tool with applications in physics, geography, medicine, chemistry, biology and more. This course offers an introduction to the basic concepts, including supervised and unsupervised learning with neural networks and methods to make the learned results interpretable. The material will be presented with scientific research applications in mind, where data has often very peculiar structure and quantitative accuracy is paramount. In the exercise class, examples will be implemented with openly available machine learning libraries.
Introduction to Machine learning for Plant Scientists
This course will introduce machine learning with emphasis on plant sciences. We will discuss topics like data pre-processing, feature extraction, clustering, regression, classification and take some first steps towards modern deep learning. The course will consist of 50% lectures and 50% hands-on programming in python, where students will directly implement learned theory as a software to help solving problems in plant sciences.