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of traffic management and control strategies in urban and freeway environments. At the same time, data-driven methodologies and machine learning offer new opportunities for optimal traffic management
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100%, Zurich, fixed-term The Chair of Space Geodesy invites applications for an exciting PhD opportunity focused on advancing research in satellite gravimetry for hydrology using machine learning
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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 Zurich We
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consortia. Good grasp of satellite- and airborne sensing, geospatial data platforms, and AI-enabled analytics, or demonstrable capacity to learn rapidly. The relevant, sector specific professional network
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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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efficiency, particularly with respect to latency. Project background The successful candidate will join the BMIC team at ETH Zurich and also be a part of the Computer Vision Lab (CVL). The project is conducted
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to positive change in society We are actively committed to a sustainable and climate-neutral university You can expect numerous benefits , such as public transport season tickets and car sharing, a wide range
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of digitalization, machine learning, analytics, and other Industry 4.0 technologies in manufacturing. Operational Excellence covers traditional industrial engineering and management topics like lean production, world
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outstanding working conditions. As part of an interdisciplinary team at the intersection of applied machine learning, behavioral science, forensic toxicology, and automotive safety, you will contribute
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society We are actively committed to a sustainable and climate-neutral university You can expect numerous benefits , such as public transport season tickets and car sharing, a wide range of sports offered