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(e.g. R or Python), statistics, machine learning, and data science. A good publication record with respect to your career stage and research interests in climate impacts in mountain regions complete your
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. This position is embedded within the SNSF Sinergia project SLIHI4BONE (Nr. 213520; project start 01.04.2023; collaboration partners: M. Bohner, RMS Foundation, Bettlach; R. Müller, ETH Zurich; E. Wehrle, ARI
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organic redox flow batteries. Close scientific interaction with a dynamic startup partner, offering insights into industrial R&D workflows and exposure to how academic research can translate into real-world
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seek candidates with strong skills in programming (e.g. R or Python), statistics, machine learning, and data science. A good publication record with respect to your career stage and research interests in
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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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and amorphous materials for space applications' Your tasks R&D in the domain of X-ray analytics, with a focus on X-ray diffraction and scattering (XRD, XRD-PDF), data analysis and modelling
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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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Swiss Federal Institute for Forest, Snow and Landscape Research WSL | Switzerland | about 1 month ago
understanding of physical and chemical processes in soils. You have experience with geospatial modeling and are proficient in a programming language relevant to data analysis (ideally R). Additionally, you
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application of statistical software, preferably R, STATA Good knowledge of national and international clinical research regulations (e.g. HFG, ICH-GCP) Excellent written and oral communication skills in German
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(target gene selection, power analyses, guide-library design, readout selection). Build, maintain, and document reproducible analysis pipelines (Python/R; Snakemake/Nextflow preferred) for novel