MSE-430: Life cycle engineering of polymersStudents understand what life cycle engineering is and apply this methodology to adapt and improve the durability of polymer-based products. They understand how to recycle these materials and are able
BIO-244: Physics of the cellLiving organisms evolve in a physical world: their cells respond to mechanics, electricity and light. In this course, we will describe the behavior and function of cells using physical principles.
AR-678: Harmony and ConflictsThis is a methodological PhD course focused on the history and description of one case study (building, drawing or projects) and the construction of its historical broader context.
HUM-485: Data in context: Critical Data Studies ILe cours "Critical Data Studies" s'inscrit dans la nouvelle offre d'enseignements TILT qui propose de croiser des savoirs provenant des SHS et des sciences de l'ingénieur afin d'aborder des thématique
AR-628: Transition workshop 2022Focusing on the cricital issues of Geneva's changing landscape, the workshop offers a concise introduction to the issues and dimensions of ecological transition by design at all scales, and a cross-di
CS-233(a): Introduction to machine learning (BA3)Machine learning and data analysis are becoming increasingly central in many sciences and applications. In this course, fundamental principles and methods of machine learning will be introduced, analy
CS-322: Introduction to database systemsThis course provides a deep understanding of the concepts behind data management systems. It covers fundamental data management topics such as system architecture, data models, query processing and op
AR-673: Transition workshopThe TW offers an educational framework to accelerate the ecological transition of the built realm. It aims to deepen the knowledge on the built environment and its sustainable development, create/tran
CS-233(b): Introduction to machine learning (BA4)Machine learning and data analysis are becoming increasingly central in many sciences and applications. In this course, fundamental principles and methods of machine learning will be introduced, analy
