486 information-security "https:" "https:" "https:" "https:" "https:" "U.S" "U.S" positions in Switzerland
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We look forward to receiving your online application through this portal and it should contain the following documents in PDF format (make sure your last name is on all the documents and in the file
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80%-100%, Lugano, fixed-term The Swiss National Supercomputing Centre (CSCS) develops and operates a high-performance computing and data research infrastructure that supports world-class science in
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staff and students are respected. Visit our Equal Opportunities and Diversity website to find out how we ensure a fair and open environment that allows everyone to grow and flourish. Sustainability is a
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ultimately fail. Our research is 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
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The UZH Global Funding Scheme supports faculties, departments, and professional service units in developing and implementing joint initiatives with international partners that advance the objectives of the UZH Global Strategy 2030. The scheme harnesses the global networking potential of the UZH...
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How does life emerge from molecules and cells? This is the central question that motivates us. With curiosity and passion, we investigate the entire spectrum ranging from the atom to the organism
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80%-100%, Zurich, fixed-term ETH Zurich | Space is dedicated to advancing space activities both within ETH and in collaboration with external stakeholders. Our mission is to position ETH Zurich as
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. Empa is a research institution of the ETH Domain. Your tasks Optimizing vehicle aerodynamics to reduce transportation emissions, understanding airborne disease transmission, and predicting climate
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. Empa is a research institution of the ETH Domain. Empa’s Laboratory Materials for Energy Conversion focuses on materials and device innovation for sustainable energy conversion and storage technologies
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frames). Project background The work focuses on data-driven generation of structural systems. You will be involved in developing, experimenting with, and evaluating machine learning models that help