Thesis projects Data and models

Quantitative methods are becoming increasingly important to understand and predict the complex interactions in crop systems. In addition, the exponential increase in computational power and data availability create numerous opportunities to enhance our methodologies. However, this comes at the expense of increasing complexity in our data and modeling workflows and the need to constantly update our toolbox. We explore how recent techniques in statistics, machine learning (AI), dynamic modelling and software development can boost our research and we aim to bridge the gap between the technical domains and our ecological and physiological research.