203 data-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "Univ" "UNIV" "Univ" "Univ" positions at ETH Zurich
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models or glioblastoma research Familiarity with transcriptomic methods (RNA-seq, FISH, spatial transcriptomics) Programming skills for data analysis (Python, R, or MATLAB) Workplace Workplace We offer
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. Our goal is to gain a better understanding of how cloud microphysical processes interact with cloud dynamics. We conduct laboratory and field studies, use remote sensing data and numerical models
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COMPAS XR framework developed at ETH Zürich. Project background The successful candidate will work at the intersection of computational design, XR, human-computer interaction, and robotic fabrication, with
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collection. This position aims to synthesise all available information from these natural fungal isolates to build hypotheses for which genetic features are essential for horizontal transfer. Job description
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and coordination experience Further information about NCCR CLIM+ can be found on our website . Questions regarding the position should be directed to Prof. Sonia I. Seneviratne, sonia.seneviratne
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research experience Contact information for reference letters from 3 referees. Please note that we exclusively accept applications submitted through our online application portal. Applications via email or
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80%, Zurich, fixed-term The Biomedical Data Science (BMDS) Lab investigates data-driven solutions for healthcare applications with a focus on neurological conditions such as spinal cord injury (SCI
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portal. The deadline for applications is the 3rd of April, 2026, with a start date of Summer-Autumn 2026. Further information about our groups can be found on the Planetology and High Pressure Group
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, NGS-based screening) Structural analysis: utilize computational structural biology tools to ensure designs maintain assembly competence and structural integrity Data integration: process and analyze
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environments (Schmidt, Science, 2022) — especially in the context of drug–host microbiome interactions — and developing dedicated tools and analytic workflows for the novel data modalities generated by Record