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data analyses using the group's existing infrastructure, as well as developing and implementing additional analysis workflows. A particular focus will be on single-cell and spatial transcriptomics
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of the optical properties of plasmonic nanoparticles using techniques such as UV-Vis and Raman spectroscopy. You will also prepare colloidal dispersions for thin film fabrication. Additionally, you will
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safety protocols. Workplace Workplace We offer Your job with impact: Become part of ETH Zurich, which not only supports your professional development, but also actively contributes to positive change in
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) or neural network-based methods. The level of the targeted problems will require further mathematical and algorithmic developments over the current state of data-driven SSM reduction. The PhD position will
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10%-30%, Zurich, fixed-term The chair of Forest Resources Management (FORM) is seeking a motivated student to assist in the development of Deep Learning approaches for tree species identification
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developing personal projects, students gain valuable hands-on experience and learn essential skills for their future. That’s why we’ve created an ecosystem where students - Bachelor’s, Master’s, and Doctoral
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dynamics using a broad range of mathematical, computational, and experimental approaches to study the population dynamics and evolution of infectious pathogens on both the within and between-host level (1 ,2
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to enable the scientists at ETH Zurich to develop new technologies necessary for their successful research. Curious? So are we. Starting date: The anticipated start date for this position is January 2026 with
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100%, Zurich, fixed-term In the newly established Brain-Body Regulation Lab at ETH Zurich (Department of Health Sciences and Technology), we focus on developing non-invasive (self-regulation
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." This project aims to develop data-driven tools to assess supply chain vulnerabilities for critical medicines, using pharmaceutical Bills of Materials (BOMs), trade flows, and production data. The work is part of