163 web-programmer-developer-"St"-"Washington-University-in-St"-"St" positions at ETH Zurich
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Student Project House (SPH) we inspire and empower students to cultivate a mindset of makers and innovators. We believe that by exploring their ideas and developing their own projects, students gain
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tools and insights for the optimal design of policies that affect electric vehicle (EV) charging and the electricity system. The PhD student will contribute to the development of exciting new methods
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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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developing personal projects, students gain valuable hands-on experience and learn essential skills for their future. That’s why we’ve created an ecosystem where students - Bachelor’s, Master’s, and Doctoral
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safety protocols. Workplace Workplace We offer Your job with impact: Become part of ETH Zurich, which not only supports your professional development, but also actively contributes to positive change in
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motivated candidate with a strong interest in material development and characterization for electrocatalytic applications. LESE is focusing on the development, characterization and advancement of (solid) CO2
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headed by Prof. Iber, which leverages imaging data to develop data-driven, mechanistic models of biological processes. The team employs cutting-edge computational tools and imaging techniques
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of the optical properties of plasmonic nanoparticles using techniques such as UV-Vis and Raman spectroscopy. You will also prepare colloidal dispersions for thin film fabrication. Additionally, you will
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) or neural network-based methods. The level of the targeted problems will require further mathematical and algorithmic developments over the current state of data-driven SSM reduction. The PhD position will
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10%-30%, Zurich, fixed-term The chair of Forest Resources Management (FORM) is seeking a motivated student to assist in the development of Deep Learning approaches for tree species identification