205 engineering-computation "https:" "https:" "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" positions at ETH Zurich
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-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 technology. We
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, molecular engineering, manufacturing and marketing. For HydroCow, we are building on an earlier developed ultra-high-throughput screening platform that allows for the rapid identifying of improved industrial
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80%-100%, Zurich, fixed-term The Center for Climate Systems Modeling (C2SM) at ETH Zurich is a joint, interdisciplinary center linking ETH Zurich with partner institutions. It provides a technology
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National Center for Tuberculosis and Lung Disease in Georgia, who will validate the technology in patient samples and perform a small pilot study. This will provide the student with the opportunity to travel
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, molecular engineering, manufacturing and marketing. For HydroCow, we are building on an earlier developed ultra-high-throughput screening platform that allows for the rapid identifying of improved industrial
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Profile Enrolled in a master’s program at a Swiss university / ETH with a strong focus on data science or statistical methods (data science, computer science, economics, social sciences, etc.) Excellent
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100%, Zurich, fixed-term Design++ is the Center for Augmented Computational Design in Architecture, Engineering and Construction (AEC) at ETH Zurich. The center's vision is to remove collaboration
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This computational project will employ calculations based on density functional theory (DFT) and extensions of DFT, such as DFT+U and DFT in combination with dynamical mean-field theory (DMFT). It is
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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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problems in scientific or engineering domains using proprietary/real data (beyond public benchmarks), where challenges like distributional generalization, multi-objective trade-offs, causality, privacy