202 developer-"https:"-"https:"-"https:"-"European-Commission"-"UCL" positions at ETH Zurich
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development for quantum key distribution and (2) TFLN circuit development for quantum enhanced precision measurements. This PhD project aims to further advance the nanofabrication of TFLN photonic circuits
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The successful PhD candidate will contribute to the scientific development, implementation, and evaluation of a mobile app. Working within a highly multidisciplinary team of psychologists
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for such purposes in a wide spectrum of industries, with significant breakthroughs in computer vision, natural language processing, and intelligent control. This PhD project aims to develop foundation models (FMs
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develops uniquely interdisciplinary design and history and theory research for landscape architecture. Through geohistorical practice, we integrate tools from natural sciences and humanities with those
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innovative methods to leverage machine learning for numerical weather forecasting and climate modeling. Project background We are looking for a motivated Machine Learning Scientist to join the development team
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at the Department of Biosystems Science and Engineering (D-BSSE) of the ETH Zurich in Basel invites exceptional candidates to apply for a PhD position in pioneering projects developing synthetic biology-inspired
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at the Department of Biosystems Science and Engineering (D-BSSE) of the ETH Zurich in Basel invites exceptional candidates to apply for a postdoctoral position in pioneering projects developing synthetic biology
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observations, from satellite to radar data. The core model will be then fine tuned for specific applications, such as high-resolution prediction over Switzerland. Job description Further develop and train the
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, development stages, and silvicultural practices) is essential for this role. The project will be carried out in a collaborative environment between the two research groups, providing extensive technical support
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postdoctoral researcher with a strong background in sequence bioinformatics, algorithms and data structures. The successful candidate will join an interdisciplinary effort developing innovative diagnostic