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NX-450: Computational neurosciences: biophysics

The course introduces students to a synthesis of modern neuroscience and state-of-the-art data management, modelling and computing technologies with a focus on the biophysical level.

CH-223: Organometallic chemistry

Basic organometallic chemistry will be covered in this course.

Structure and bonding in organometallic compounds.
reactivity of organometallic compounds, stoichiometric reactions, catalyzed rea

MATH-451: Numerical approximation of PDEs

The course is about the derivation, theoretical analysis and implementation of the finite element method for the numerical approximation of partial differential equations in one and two space dimens

FIN-406: Macrofinance

This course provides students with a working knowledge of macroeconomic models that explicitly incorporate financial markets. The goal is to develop a broad and analytical framework for analyzing the

ME-201: Continuum mechanics

Continuum conservation laws (e.g. mass, momentum and energy) will be introduced. Mathematical tools, including basic algebra and calculus of vectors and Cartesian tensors will be taught. Stress and de

CH-438: Total synthesis of natural products

Complex polycyclic natural products are chosen to illustrate the evolution of the state-of-the-art of the field, the interplay between strategy and new reactions as well as the importance of implement

PHYS-702: Advanced Quantum Field Theory

The course builds on the course QFT1 and QFT2 and develops in parallel to the course on Gauge Theories and the SM.

ChE-605: AI in chemistry and beyond:Highlights in the field

Should have expertise in chemistry, physics or lite and material sciences. Although a very good knowledge in Al-based algorithms is required to fully understand the technical details, a basic knowledg

ChE-408: Process intensification and green chemistry

The first part of the course (~20%) is devoted to green chemistry and life cycle assessment. The remainder focuses on process intensification (fundamentals, detailed description of a few selected te

PHYS-754: Lecture series on scientific machine learning

This lecture presents ongoing work on how scientific questions can be tackled using machine learning. Machine learning enables extracting knowledge from data computationally and in an automatized way.