This summer school is a hybrid event and is subdivided into an online phase and a hybrid phase (attendance phase or live online phase). participants can decide to follow the course online and on site or 100% virtually. The online phase with pre-recorded lectures introduces the basics in machine learning, focusing on 3D voxelized geometries, its most frequent applications, and methodological as well as ethical aspects. The live online and attendance phases will then expose how machine learning may interfere radiotherapy workflows in detail. The knowledge of deep learning methodologies for image synthesis, organ and target segmentation, and image registration in the context of radiotherapy will be expanded. Furthermore, applications in computational dosimetry and plan optimization will be discussed, ranging from dose prediction, guided plan optimization, and treatment outcome prediction. The summer school is designed for PhD/MD, MSc or BSc students. More information on our website: www.dkfz.de/summer_school2023_de.