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100%, Zurich, fixed-term Human–Computer Interaction in Architecture and Digital Fabrication This fully funded, full-time PhD position spans four years and is embedded within the interdisciplinary
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. The goal is to establish structure-biodegradability relationships by linking polymer physicochemical properties (e.g., molecular weight, backbone chemistry, side chain chemistry) and system characteristics
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scale description of interfaces with an application to nucleation phenomena. The MET group at ETH Zurich, led by Philipp Rehner, is dedicated to linking rigorous physical molecular models to the design of
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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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establish (semi-)quantitative polymer structure–adsorption relationships by linking polymer and sorbent properties to experimentally collected adsorption and desorption data. Specific tasks include: Conduct
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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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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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project would link to ongoing research and facilities at ITA or LUS (max. 2500 words excl. references), as a PDF. CV, project and publication list, highlighting selected projects and publications
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-facturing processes. In this internship, you will work on state-of-the-art anomaly detection methods using computer vision and time-series data, with a particular focus on multimodal data fusion for powder
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quality Surrogate Modeling: Building, training, and evaluating machine learning surrogate models to emulate complex seismic behaviors and accelerate forecasting Data Engineering: Populating and managing