247 computational-physics-"https:"-"https:"-"https:"-"https:" positions in Switzerland
Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Employer
-
Field
-
DIZH understands innovation very broadly and includes all disciplines: artistic, design, natural science, technology, humanities, education and social science.
-
that will shape your research career. Your profile We are looking for 2 highly motivated PhD students with a strong analytical background and an MSc degree in Physics, Computational Chemistry, Materials
-
fundamental discoveries in biology and medicine as well as several Nobel Laureates. Become part of our community! In Prof. Torsten Schwede's group, we use computational methods, with a strong focus on
-
80%-100%, Zurich, fixed-term We are seeking a talented Research Engineer with strong expertise in Computer Graphics, physically-based simulation, and high-performance implementation. In this role
-
molecular-scale continuum description of inhomogeneous systems – in process design and, therefore, to fuse the scales from molecules to processes. To overcome the computational challenge of applying molecular
-
100%, Zurich, fixed-term The Computational Design Lab is an interdisciplinary research group at ETH Zurich, led by Prof. Dr. Bernd Bickel . We develop novel algorithms and next-generation
-
the power of both classical and quantum computing resources? How can we exploit or take inspiration from quantum physics to develop cutting-edge machine learning? Your work will encompass a diverse array of
-
agreement. We develop computational methods to accelerate materials discovery through defect engineering, with a focus on extreme environments. Application areas include fusion reactors, hydrogen systems, and
-
cell biology, and systems-level quantitative biology. The project aims to uncover how mechanical properties, forces, and physical phenotypes integrate with molecular networks to regulate the function
-
driven by curiosity about the physical mechanisms that underlie failure and by the ambition to translate this understanding into more reliable and resilient materials and structures. By combining numerical