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, electrical engineering and computer science to design highly efficient and sensitive imaging and inference approaches to help guide diagnosis and treatment in cardiovascular patients. Project background Our
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Required experience: CH/EU/EFTA citizenship or a valid work permit for Switzerland A Master’s degree (ETH, university) in engineering, computer science, or a related field Strong academic performance meeting
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degree in the fields of transportation, civil engineering, computer science, urban analytics, spatial planning, geography, geoinformation, psychology or an equivalent qualification. Experience with first
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the ETH Zurich employee benefits program chevron_right Working, teaching and research at ETH Zurich We value diversity In line with our values , ETH Zurich encourages an inclusive culture. We promote
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trait-associated sequence variation. We offer a PhD position at the interface of computational and statistical genomics, and bioinformatics. Project background Cattle are an interesting «model organism
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Zurich is a community of approximately 50 researchers from more than 20 countries working on the development of methods and computational tools for automation, exploring their potential for promoting our
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80%-100%, Zurich, fixed-term The Biomaterials Engineering research group at the Institute for Biomechanics (IfB), D-HEST, ETH Zurich, develops biomaterials and advanced biomanufacturing systems for in vitro disease modeling. Our group integrates mechanical design, materials science, and...
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80%-100%, Zurich, fixed-term The Functional Genomics Center Zurich (FGCZ) is a joint state-of-the-art research and training facility of the ETH Zurich and the University of Zurich. With the latest technologies and key expertise for omics research, the FGCZ provides research services and project...
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care work, part-time employment, or career breaks and consider applications proposing joint research in job-sharing. With its early-career fellowship program, the Collegium nurtures an environment
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Emulators of Stochastic computational models"), funded by the Swiss National Science Foundation (SNSF). The project aims to significantly advance the state-of-the-art in uncertainty quantification (UQ) by