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conventional trade statistics. Our methodology is designed to be highly scaleable and could be extended to other domains. The project provides a data-driven foundation for assessing supply chain resilience in
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micrometeorology, greenhouse gas exchange, tree and/or ecosystem physiology Relevant research experience can be based on observations, modelling or statistical analyses Excellent command of large data analyses as
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quantitative statistical analysis Prior research experience is preferred You should be highly motivated to conduct independent research on educational approaches to misinformation You must be a highly committed
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testing, including calibration, repeatability, humidity/interference effects, aging, and statistical evaluation across sensor batches Collaborate closely with interdisciplinary teams (materials science
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atmospheric/environmental sciences, physics, computational science, engineering or a related field A background in numerical modelling, statistical data analysis and/or programming skills is highly encouraged
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will be put in place. Profile The ideal candidate will hold a PhD or equivalent in bioinformatics, computational biology, computer science, applied statistics, or a related field, with substantial (>6
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experience in managing plant growth facilities, in cultivating plants, microscopy, experimental design, statistical analysis and have knowledge on high-throughput image analysis, and hold a valid driver's
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12 Dec 2025 Job Information Organisation/Company University of Basel Research Field Biological sciences » Biology Computer science » Other Mathematics » Statistics Neurosciences » Neurology
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quantitative analysis. Experience with statistical modelling; familiarity with or interest in machine‑learning approaches is an advantage, but not a requirement. Excellent written and spoken English
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stable water isotope data, and Statistical analyses, including machine learning approaches. The full-time position is funded for four years. Salary and social benefits are provided according to ETH Zurich