153 machine-learning-"https:" "https:" "https:" "https:" "https:" "https:" "Simons Foundation" uni jobs at ETH Zurich in Switzerland
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the power of both classical and quantum computing resources? How can we exploit or take inspiration from quantum physics to develop cutting-edge machine learning? Your work will encompass a diverse array of
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methods. Contributing to the development, adaptation, and application of machine‑learning models tailored to RODI data (in collaboration with project partners). Designing and implementing an innovative
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Master’s degree in Computer Science, AI, Machine Learning, Mathematics, Electrical Engineering, or a closely related field; or Master’s degree in Medicine (MD) with strong Python skills and some ML
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, which not only supports your professional development, but also actively contributes to positive change in society You can expect numerous benefits , such as public transport season tickets and car
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upcoming areas off the beaten paths. Our three main areas of research are machine learning, distributed systems, and theory of networks. Within these three areas, we are currently working on several projects
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tickets and car sharing, a wide range of sports offered by the ASVZ , childcare and attractive pension benefits chevron_right Working, teaching and research at ETH Zurich We value diversity and
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(preferably Python), multiple years of programming experience as well as profound knowledge of professional computer-aided design and 3D modelling In addition, you have experience in CAD/CAM (preferably McNeel
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) or equivalent in civil, mechanical or electrical engineering, geosciences, physics, applied mathematics, computer sciences or related fields, and be at the beginning of their research career. Principal
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100%, Zurich, fixed-term Human–Computer Interaction in Architecture and Digital Fabrication This fully funded, full-time PhD position spans four years and is embedded within the interdisciplinary
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space applications. We combine theory, physics-based simulations, machine learning, and autonomous workflows to understand and design materials that can perform under conditions where conventional