217 computer-science-intern-"https:"-"https:"-"https:"-"https:"-"CUBO" positions at ETH Zurich
Sort by
Refine Your Search
-
90%, Basel, permanent The Laboratory Automation Facility (LAF) is a central research and service platform within the Department of Biosystems Science and Engineering (D-BSSE) at ETH Zurich
-
that the pre-selection is carried out by the responsible recruiters and not by artificial intelligence. About ETH Zürich ETH Zurich is one of the world’s leading universities specialising in science and
-
physics simulation, rendering, and neural graphics. Profile Bachelor’s, Master’s, or PhD in Computer Science, Computer Graphics, or a related field. Strong proficiency in C++ and Python, with a track record
-
100%, Basel, fixed-term A World-Class Research Environment at the Nexus of Biology, Engineering, and Physical Sciences The Biotechnology and Bioengineering group led by Prof. Dr. Martin Fussenegger
-
100%, Basel, fixed-term A World-Class Research Environment at the Nexus of Biology, Engineering, and Physical Sciences The Biotechnology and Bioengineering group led by Prof. Dr. Martin Fussenegger
-
The Albert Einstein School of Public Policy at ETH Zurich is an interdisciplinary centre that combines public policy, science and technology to address the greatest societal challenges of our time
-
is carried out by the responsible recruiters and not by artificial intelligence. ETH Zurich is one of the world’s leading universities specialising in science and technology. We are renowned for our
-
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
-
atmospheric/environmental sciences, physics, computational science, engineering or a related field A background in numerical modelling, statistical data analysis and/or programming skills is highly encouraged