231 machine-learning-"https:" "https:" "https:" "https:" "https:" "UCL" uni jobs in Switzerland
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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
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applied project frameworks in urban transformation. You can expect numerous benefits , such as public transport season tickets and car sharing, a wide range of sports offered by the ASVZ , childcare and
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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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worked in or with the defence sector Has programming experience in Python and Pyomo Due to the position’s close collaboration with the Swiss defence industry and the armed forces, preference will be given
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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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of computer graphics fundamentals, numerical methods, and GPU/parallel computing concepts. Experience with at least one major deep learning framework (PyTorch preferred). Excellent problem-solving skills and
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, neuroscientists, computer scientists, clinicians, and data scientists across the Singapore-ETH Centre (SEC), the National University of Singapore (NUS), and Nanyang Technological University (NTU), the PhD student
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engineering, or a related field 5+ years of experience in spacecraft avionics engineering Experience with onboard data handling systems, avionics buses, and subsystem interfaces Knowledge of embedded software
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Computational Design Lab and work at the interface of computer vision, computer graphics, hardware, and extended reality. The project is part of ETHAR, a new research initiative at ETH Zürich with a unique focus