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culture, and flow cytometry preparation of deep sequencing libraries for functional genomics experiments bioinformatics, statistics, and programming The candidate must have a strong motivation and interest
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mathematics Mathematics » Statistics Technology » Biotechnology Researcher Profile First Stage Researcher (R1) Country Switzerland Application Deadline 1 May 2024 - 23:59 (Europe/Zurich) Type of Contract
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studies water and climate extremes in mountain regions under global change. We have strong expertise in hydrology, climate sciences, extreme value analyses, statistical modelling, and climate impact
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ETH Zurich studies water and climate extremes in mountain regions under global change. We have strong expertise in hydrology, climate sciences, extreme value analyses, statistical modelling, and climate
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. The candidate will have the opportunity to exploit some of the cutting-edge experimental and computational methods, comprising constraint-based and kinetic modeling, statistical analysis of large datasets, high
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Swiss Federal Institute for Forest, Snow and Landscape Research WSL | Switzerland | about 2 months ago
taxonomy and are highly motivated to analyze ecological data statistically. Furthermore, you are scientifically creative and interested in interdisciplinary research with project partners from very different
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. The candidate will have the opportunity to exploit some of the cutting-edge experimental and computational methods, comprising constraint-based and kinetic modeling, statistical analysis of large datasets, high
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, implementing and applying new inference methods in computational Bayesian phylolinguistics. The overarching goal is to develop the statistical and computational tools necessary to answer key questions in
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, such as bacteriohopanepolyols. The research will require an interest in applying mass spectroscopic techniques, statistical approaches to develop calibrations, and generate environmental reconstructions
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method. You have rigorous statistics training in causal inference, and a strong command of Stata and/or R (knowledge of machine learning methods is a plus). You have, at the time of appointment, completed