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, or HCI methods familiarity with adaptive systems or machine learning prior experience conducting user studies Beneficial background in computational interaction or adaptive systes knowledge of optimization
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20%-40%, Zurich, fixed-term The Public Policy Group at ETH Zurich invites applications for a research assistant in quantitative social science for a project using machine learning to improve refugee
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system design. We employ advanced computational methods, machine learning, modeling, and custom hardware and software to continually test our solutions in various real-world industry projects. In one
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Mixed Reality. This research combines physiological time series analysis (such as or similar to EEG, EMG, EOG), machine learning, and real-time system design for intelligent interaction systems
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main areas of research are machine learning, distributed systems, and the theory of networks. Within these three areas, we are currently working on several projects: graph neural networks, natural
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understanding and practical experience with machine learning approaches for biomarker discovery and predictive modeling, specifically with hands-on experience in developing and applying neuronal networks
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informatics, especially chronic disease management (with emphasis on asthma) Machine learning / deep learning / artificial intelligence Profile Ideally, the candidate has a degree in Electrical Engineering and
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experience CH/EU/EFTA citizenship or a valid Swiss work permit Master’s degree (ETH, university) in engineering, mechatronics, computer science, or a related field Experience in machine learning, signal
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benefits , such as public transport season 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
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vehicles. Another research focus is on solid-state pulse modulators for medical applications (computer tomography/cancer treatment) and accelerators (CERN). For the design and optimisation of the various