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most of the following: Bachelor's or (preferably) Master's degree in Computer Science, Engineering or a Social Science discipline combined with solid engineering skills 1–2 years of relevant work
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20%-30%, Zurich, fixed-term Our research team at KOF, ETH Zurich is seeking a student assistant to contribute to the project "Computing Resilience Indicators for Pharmaceutical Supply Chains
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the impact of alloying on the magnetic properties of Sm-Co magnets, using Fe-Cr as a test bed material. This project combines advanced experimental techniques with computational modeling, including: Advanced
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Key Qualifications Masters- or doctorate-level degree in computer science, data science, electrical engineering, computational biology, microbiology, statistics, or other relevant fields Proficient
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. Profile The ideal candidate will be a computer science student or a student with extensive practical programming experience. Interest in the social sciences and law is a big advantage. Workplace Workplace
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dynamics using a broad range of mathematical, computational, and experimental approaches to study the population dynamics and evolution of infectious pathogens on both the within and between-host level (1 ,2
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interconnected systems in order to support sustainable urban development and the well-being of their inhabitants. Project background This dissertation is part of the National Research Programme 81 (NRP 81
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The Professorship of International Relations and Data Science is currently seeking a postdoctoral researcher for a two-year position (100%). The position is based at ETH Zurich and is supervised by Prof. Livia Schubiger. The candidate will work with the IRDS group on projects that leverage NLP,...
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and a computational design and robotic WAAM (wire arc additive manufacturing) fabrication framework for facilitating the reuse of end-of-life steel sections. This will be achieved by tasks related to (i
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position (~4 years) in a great scientific and social environment at a world leading University (see below). The project will equally combine lab work and computational analysis of the acquired data and