202 data-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "UNIV" "Univ" "UNIV" "UNIV" positions at ETH Zurich in Switzerland
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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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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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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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, 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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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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portal. The deadline for applications is the 3rd of May, 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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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
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information for two references, which can be appended to the CV or provided as a separate PDF if you prefer. No reference letters are needed at the time of application, and we will notify you in advance if we
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. ENDOTRAIN will train a new generation of interdisciplinary experts who merge clinical endocrinology, artificial intelligence, data science, engineering, ethics and law into an integrated field of digital
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problems in scientific or engineering domains using proprietary/real data (beyond public benchmarks), where challenges like distributional generalization, multi-objective trade-offs, causality, privacy