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to mechanistically constrain the climatic and anthropogenic controls on greenhouse-gas (i.e., carbon dioxide, methane, and nitrous oxide) emissions in Tumba-Ngiri-Maindombe, a severely understudied region that houses
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), digital image/volume correlation and targeted manipulation of polymeric chains (i.e., mechanophore additions) to gain a deeper insight into the failure process of polymeric rubbers. The PhD student will
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technologies (i.e. computing, data, algorithms, AI) in society. We are in particular looking for candidates who have interest and experience with STS and humanities pedagogy in the context of a technical
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The healthcare systems of the future must harness data effectively to support clinicians, allowing them to focus on patient care while leveraging AIto detect patterns beyond human perception
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80%-100%, Zurich, fixed-term The Swiss Data Science Center (SDSC) is a national research infrastructure in data science and artificial intelligence (AI) of the ETH domain, with EPFL and ETH Zurich
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100%, Zurich, fixed-term The postdoctoral researcher will advance the application of AI, large language models (LLMs), and machine learning to extract trustworthy climate information from large
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research groups at ETH Zurich, the Swiss Data Science Center and Agroscope. The overall objective of PhenoMix is to test the hypothesis that current high throughput field phenotyping (HTFP) technology in
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and networking platform to support the development and application of Earth system, weather, and climate modeling, data infrastructure, and impact research. Project background There is an ever
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research groups at ETH Zurich, the Swiss Data Science Center and Agroscope. The overall objective of PhenoMix is to test the hypothesis that current high throughput field phenotyping (HTFP) technology in
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novel multi-encoder-decoder architectures capable of ingesting various satellite data streams (e.g. radiances, cloud products, lightning observations, hyperspectral soundings) and integrating them