208 structural-engineering-"https:"-"https:"-"https:"-"https:"-"Dip" positions at ETH Zurich
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concepts into clear, engaging visuals - working closely with our engineering team to bring ideas to life. The scope of the work could be 60% for one project or with the right candidate and skill set extended
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, electrical engineering, a natural science, medical, or related field Experience in scientific research, ideally in the area of machine learning and/or data science Strong organizational skills and an
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and engineering the structure, function, and dynamics of microbiomes across diverse biological and environmental systems. Several research groups at the Institute of Microbiology contribute to the NCCR
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for world class research in the field of robotic fabrication in architecture and construction. Job description We are looking for a highly skilled software engineer to work on the development of python
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100%, Zurich, fixed-term The Technology Marketing Group , founded by Florian von Wangenheim in 2013, is a pioneering research group at ETH Zurich dedicated to exploring the intersection of marketing
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opportunity to work with leading experts across Europe to design and deliver sustainable meta-materials for vibration mitigation, self-aware meta-components and carbon-efficient meta-structures
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of semiconductor devices. The aim is to predict these properties for arbitrarily large structures, at a DFT-level of accuracy. As a starting point, you will extend the large-scale equivariant GNNs we develop
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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
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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
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-project will be closely supervised by Prof. Hubert Pausch at ETH Zurich. The second candidate will focus on imputation and association testing. Approaches to impute structural variants into large mapping