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CH-341: Physical chemistry of interfaces

Acquire an understanding of interfacial phenomena, micro-heterogeneous colloidal solution systems and dynamic electrochemistry.

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.

BIOENG-448: Fundamentals of neuroengineering

Neuroengineering 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

BIO-615: Neural circuits for reward and aversion learning

Animals must learn from past experiences, to adapt their behavior to an ever-changing environment. Students will learn about the neuronal circuit mechanisms of reward-based learning, and of aversively

BIO-465: Biological modeling of neural networks

In this course we study mathematical models of neurons and neuronal networks in the context of biology and establish links to models of cognition. The focus is on brain dynamics approximated by determ

MSE-806: Spin-based devices for neuromorphic computing

The course entails a 5-days-program with lectures and exercises about spin-based computing and novel spin texture-based computing devices. An additional round table discussion and journal club session

MICRO-514: Flexible bioelectronics

The course is an introduction to the emerging field of flexible (bio)electronics. It provides an overview of the materials and processes used to design and manufacture flexible circuits and sensors.

MICRO-560: BioMEMS

This course covers the main applications of micro devices for life science and biomedical applications. The course is organized by application topic. It is also covering the basic physical, biological

BIO-696: Neuronal circuits underlying goal-directed behavior

The brain can be viewed as a network of neurons receiving sensory input and carrying out experience- and context-dependent computations through complex synaptic interactions to drive motor output, i.e

CS-434: Unsupervised & reinforcement learning in neural networks

Learning is observable in animal and human behavior, but learning is also a topic of computer science. This course links algorithms from machine learning with biological phenomena of synaptic plastic