86 programming-"https:"-"Inserm"-"FEMTO-ST" "https:" "https:" "https:" "https:" "https:" "P" "St" positions at ETH Zurich
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articles, not programming). This position offers an excellent opportunity to learn basic methods of meta-analysis, get an overview of an educational field that is of growing interest, and gain quantitative
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for emulating constrained optimization problems Advanced programming skills in Python, with deep experience in libraries such as PyTorch, Pyomo, and the broader scientific stack (Xarray, Pandas). Knowledge
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2026, with a 100% workload, based in Zurich, and is fixed-term for three and a half years. Working across sociocultural, political-economic, and theoretical contexts, the LUS Doctoral Program fosters
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related field with experience in water chemistry, silviculture, experimental field work and large-scale data analysis. You must have good statistical skills and programming experience (e.g., in R or Python
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of Competence in Research (NCCR) Separations. Job description Within a broader research program that integrates process modelling, computational materials screening and discovery, experimental synthesis, and
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or Master's level) Interest in geophysics, civil engineering, or data-driven infrastructure monitoring Practical, hands-on attitude for field and laboratory work Programming experience (Python preferred
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qualifications include strong analytical and quantitative skills in numerical analysis, programming, high-performance computing, as well as skills in dynamics & structural health monitoring, data analysis and
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researcher to advance our understanding of magmatic and volcanic systems. Job description Develop and lead an independent research program in magmatic petrology, volcanology, and/or geochronology. Publish
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As a PhD student, you will plan, generate, and interpret new research data; you will present data to scientific colleagues in workshops and conferences, and you will prepare your research findings
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to projects within the NCCR Microbiomes. The NCCR Microbiomes is a nationwide, interdisciplinary research programme, bringing together experimental and computational researchers with the aim of understanding