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position in the area of Machine Learning for Engineering Design under the guidance of Prof. Mark Fuge, the Chair of Artificial Intelligence in Engineering Design. The general area of the laboratory covers
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Mixed Reality. This research combines physiological time series analysis (specifically EMG during muscle activation), machine learning, and real-time system design for intelligent interaction systems
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Metagenomics, meta-transcriptomics and metabolomics data analysis and familiarity with gut microbiome research. Machine learning for genomics (representation learning, generative models, causal inference). Multi
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, 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 Zurich We
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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 chevron_right Working, teaching and
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classical approaches and machine learning. We look forward to strengthening our team with a colleague who contributes to our research and teaching, and is interested in gaining more experience and expanding
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main areas of research are machine learning, distributed systems, and the theory of networks. Within these three areas, we are currently working on several projects: graph neural networks, natural
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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 diversity and
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experience CH/EU/EFTA citizenship or a valid Swiss work permit Master’s degree (ETH, university) in engineering, mechatronics, computer science, or a related field Experience in machine learning, signal
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Publication list Contact details of two refereesPlease send your application to [nicola.serra+sinergia@uzh.ch]. Further information about [Department of Mathematical Modeling and Machine Learning or Department