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ETH Zurich, Mathematics Position ID: 1118-PDAPDE [#26975] Position Title: Position Type: Postdoctoral Position Location: Zurich, Zurich 8092, Switzerland [map ] Subject Area: Analysis and Partial
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Research Assistant / HiWi (8 hours/week) - Climate Opinion Data Analysis with R - Faculty of Busines
Research Assistant / HiWi (8 hours/week) - Climate Opinion Data Analysis with R - Faculty of Busines The research group of International Political Economy and Energy Policy, led by Prof. Aya Kachi
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results and conduct analytical modelling and numerical simulations (e.g., finite element modelling) to support experimental findings and predict performance. Independently implement and execute the research
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results and conduct analytical modelling and numerical simulations (e.g., finite element modelling) to support experimental findings and predict performance. Independently implement and execute the research
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of our Materials Vision Tech initiative, we focus on multi-element gradient thin film systems, i.e. their rapid deposition and automated multi-technique characterization. Within the Swiss-Polish innovation
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Thun explores the possibility of high throughput materials development. In the context of our Materials Vision Tech initiative, we focus on multi-element gradient thin film systems, i.e. their rapid
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pathogens such as viruses, bacteria, and fungal spores. Current approaches are slow and labor-intensive, often relying on culture-based analysis that requires several days. This project aims to further design
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cutting edge research work, develop novel computational tools and integrate new strategies for the safe and sustainable use of chemicals and materials. Your tasks Large-scale data analysis, programming and
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property analysis, sorting, and grading. Contribute to the TIMBERHAUS project by applying advanced image processing and AI methods for timber quality assessment. Integrate experimental data with
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to develop a research project that fits into the broad scope of bacteria-jumbophage interactions PhD or equivalent degree with ideally a strong component in any of the following areas: microbiology