FIN-609: Asset Pricing (2011 - 2024)This course provides an overview of the theory of asset pricing and portfolio choice theory following historical developments in the field and putting
emphasis on theoretical models that help our unde
MATH-489: Number theory II.c - CryptographyThe goal of the course is to introduce basic notions from public key cryptography (PKC) as well as basic number-theoretic methods and algorithms for cryptanalysis of protocols and schemes based on PKC
MATH-436: Homotopical algebraThis course will provide an introduction to model category theory, which is an abstract framework for generalizing homotopy theory beyond topological spaces and continuous maps. We will study numerous
PHYS-641: Quantum ComputingAfter introducing the foundations of classical and quantum information theory, and quantum measurement, the course will address the theory and practice of digital quantum computing, covering fundament
PHYS-512: Statistical physics of computationThe students understand tools from the statistical physics of disordered systems, and apply them to study computational and statistical problems in graph theory, discrete optimisation, inference and m
MSE-238: Structure of materialsIntroduction to materials structure including crystallography, the structure of amorphous materials such as glasses, polymers and biomaterials as well as the basics of characterization techniques.
MATH-444: Multivariate statisticsMultivariate statistics focusses on inferring the joint distributional properties of several random variables, seen as random vectors, with a main focus on uncovering their underlying dependence struc
MSE-209: Transfer phenomena in materials scienceCe cours porte sur le transfert de la chaleur par conduction, convection et rayonnement, ainsi que sur la diffusion à l'état solide. D'après les règles phénoménologiques (Equations de Fourrier et Fick
PHYS-467: Machine learning for physicistsMachine learning and data analysis are becoming increasingly central in sciences including physics. In this course, fundamental principles and methods of machine learning will be introduced and practi