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to exploit some of the cutting-edge experimental and computational methods, comprising constraint-based and kinetic modeling, statistical analysis of large datasets, high-throughput metabolomics, time-lapse
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Environmental science » Other Mathematics » Statistics Researcher Profile Recognised Researcher (R2) Country Switzerland Application Deadline 9 Mar 2026 - 22:59 (UTC) Type of Contract Permanent Job Status Full
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. For both projects, skills in statistical data analyses are important. You enjoy engaging with ideas in depth and are motivated by understanding concepts rather than simply completing tasks. You are willing
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Environmental science » Earth science Environmental science » Other Mathematics » Statistics Researcher Profile Recognised Researcher (R2) Country Switzerland Application Deadline 23 Feb 2026 - 22:59 (UTC) Type
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skills in quantitative data collection, management, and statistical analysis Excellent coding and programming skills (e.g., Python, R, Stata) Strong interest in research in the fields of sustainability
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in planning and conduction of patient-oriented, clinical research projects Very good knowledge of clinical and/or epidemiological study methodology and design Good knowledge in statistical methods and
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conferences. Enjoy protected research time to pursue independent research interests. Required: PhD in Marketing/Business/Analytics (or a related field); strong statistical background; proficiency in Python
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Swiss Federal Institute for Forest, Snow and Landscape Research WSL | Switzerland | about 1 month ago
assessments (e-DNA metabarcoding), bioinformatics and multivariate statistical analyses, and/or experimental planning. Furthermore, we expect very good knowledge in R programming, a good command of English, as
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isotope analysis, or ecophysiology. Demonstrated experience with ecological datasets, statistical analysis, and/or provenance trial experiments. Excellent organizational, communication, and collaborative
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PhD degree in Biology or Environmental Sciences and have a strong background in multivariate statistical analyses, chemical ecology, plant-herbivore interactions and experimental planning. Furthermore