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, the candidate should be committed to: doing field work, wet-lab work, learning about bioinformatics, including R and shell programing, and analyzing data using population genetics tools and theories
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, or conservation genetics. In addition to an interest in evolutionary and conservation biology, the candidate should be committed to: doing field work, wet-lab work, learning about bioinformatics, including R and
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Science or related field Strong skills in quantitative methods and a strong command of R or another statistical programme Motivation to conduct independent research on your PhD as well as work together
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-culture approaches, and skilled in fluorescence microscopy and image analysis for functional read-outs of microphysiological systems Software: Proficiency in Python, MATLAB, or R for data analysis, and
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: collaboration partners: J. Löffler, ETH Zürich; K. Klein, Universität Zürich; R. Müller, ETH Zürich, B. Schaller, Universitätsspital Bern) focusing on the development of advanced organotypic in vitro bone models
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. Candidates should be able to independently conduct statistical analyses in R, be able and willing to conduct fieldwork in the Swiss Alps, and have knowledge in plant species identification. Prior experience
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should have experience and knowledge in plant species identification. The successful candidate should be able to independently conduct statistical analyses in R and hold a valid driver's license
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, or similar Proficient knowledge of and previous experience with R and Python, survey design, experimental design, field experiments and quasi - experiments are an added value Strong interest to work in
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analytical and quantitative skills, including proficiency in statistical software (e.g., Python, R). Demonstrated interest in climate change, sustainable finance, and corporate sustainability. Strong written
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knowledge in plant species identification. The successful candidate should be able to independently conduct statistical analyses in R and hold a valid driver's license. Experience in GIS and handling large