212 engineering-computation "https:" "https:" "https:" "https:" "https:" "https:" "University of St" positions at ETH Zurich
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compromise grid reliability and energy security. We proceed in two steps. First, we use AI-based document analysis and engineering data to construct detailed bills of materials (BOMs) for selected critical
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of the world’s leading universities specialising in science and technology. We are renowned for our excellent education, cutting-edge fundamental research and direct transfer of new knowledge into society. Over
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specialising in science and technology. We are renowned for our excellent education, cutting-edge fundamental research and direct transfer of new knowledge into society. Over 30,000 people from more than 120
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for diverse applications in the field of bio- and nano-technology. For this position, a project on the synthesis of imaging probes, targeting peptides and therapeutic molecules and covalent functionalization
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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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, 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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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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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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problems in scientific or engineering domains using proprietary/real data (beyond public benchmarks), where challenges like distributional generalization, multi-objective trade-offs, causality, privacy