BIOENG-450: In silico neuroscience"In silico Neuroscience" introduces students to a synthesis of modern neuroscience and state-of-the-art data management, modelling and computing technologies.
ENG-421: Fundamentals in systems engineeringIntroduction to systems engineering using the classical V-model. Topics include stakeholder analysis, requirements definition, concept selection, design definition and optimization, system integration
BIOENG-448: Fundamentals of neuroengineeringNeuroengineering is at the frontier between neuroscience and engineering: understanding how the brain works allows developing engineering applications and therapies of high impact, while the design of
MICRO-211: Analog circuits and systemsThis course introduces the analysis and design of linear analog circuits based on operational amplifiers. A Laplace early approach is chosen to treat important concepts such as time and frequency resp
MATH-495: Mathematical quantum mechanicsQuantum mechanics is one of the most successful physical theories. This course presents the mathematical formalism (functional analysis and spectral theory) that underlies quantum mechanics. It is sim
MATH-425: Spatial statisticsIn this course we will focus on stochastic approaches for modelling phenomena taking place in multivariate spaces. Our main focus will be on random field models and on statistical methods for model-ba
MICRO-461: Low-power radio design for IoTThe basic function of an IoT node is to collect data and send it through a wireless channel to the cloud. Since the power consumption of an IoT node is largely dominated by the wireless communication,
