218 machine-learning-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"ISCTE-IUL" positions in Switzerland
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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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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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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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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
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Master’s students of national and international institutions Strong motivation to explore topics in human–computer interaction, learning technologies, and AI-assisted tools Experience or strong interest in
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100%, Zurich, fixed-term We have an open PhD position at the intersection of machine learning, embedded intelligence and human–computer interaction. The project will explore how learning systems can