Cours

CH-411: Cellular signalling

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MSE-304: Surfaces and interfaces

This lecture introduces the basic concepts used to describe the atomic or molecular structure of surfaces and interfaces and the underlying thermodynamic concepts. The influence of interfaces on the p

MSE-305: Introduction to atomic-scale modeling

This course provides an introduction to the modeling of matter at the atomic scale, using interactive Jupyter notebooks to see several of the core concepts of materials science in action.

BIO-468: Scientific literature analysis in computational molecular biology

The goal of this course is to learn to analyze a scientific paper critically, asking whether the data presented support the conclusions that are drawn. The analysis is presented in the form of a summa

ChE-402: Diffusion and mass transfer

This course aims to provide an in-depth understanding of diffusion and mass transfer, an essential tool for the chemical engineers.

BIO-488: Scientific project design in translational oncology

The theme of the course is the role of inflammation in cancer. It focuses on the regulation and multifaceted functions of tumor-associated inflammatory cells, and how they promote or oppose cancer.

PHYS-201(c): General physics : electromagnetism

Introduction à la mécanique des fluides, à l'électromagnétisme et aux phénomènes ondulatoires.

COM-404: Information theory and coding

The mathematical principles of communication that govern the compression and transmission of data and the design of efficient methods of doing so.

MSE-437: Polymer chemistry and macromolecular engineering

Know modern methods of polymer synthesis. Understand how parameters, which determine polymer structure and properties, such as molecular weight, molecular weight distribution, topology, microstructure

MATH-205: Analysis IV - Lebesgue measure, Fourier analysis

Learn the basis of Lebesgue integration and Fourier analysis

MATH-432: Probability theory

The course is based on Durrett's text book Probability: Theory and Examples.
It takes the measure theory approach to probability theory, wherein expectations are simply abstract integrals.