178 machine-learning "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" positions at ETH Zurich
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, qualitative methods that combine situated ethnographic detail with deep knowledge of cultural and political contexts and histories, ideally in a cross-national comparative perspective. You can learn more about
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in society 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 attractive pension benefits Start date
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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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component of solid-state transformers (SSTs). Such SSTs are required, for example, in future AI data centres, where power consumption per computer rack increases to levels of several hundred kilowatts or even
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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 value
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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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equality of opportunity, value diversity and nurture a working and learning environment in which the rights and dignity of all our staff and students are respected. Visit our Equal Opportunities and
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for highly motivated, committed, creative and eager to learn individuals, able to work in a team and with excellent communication skills. Working in a top-level research environment with advanced laboratory
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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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deep learning workflows for tree species mapping. The position contributes to building a scalable system for forest monitoring by refining model performance and ensuring high quality geospatial data