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Phase-0, the candidate will contribute to detailed data analysis, student supervision, and the dissemination of scientific results. The data obtained will advance our understanding of nuclear shape
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! PROJECT: The project entitled ‘Dynamic cues guiding postnatal germline development in marmoset‘ focuses on single-cell transcriptome analysis of germ cell development in a non-human primate model. In
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or a related discipline A solid background in climate and atmospheric sciences, and extreme weather ideally supported by knowledge of machine learning and time series analysis is of advantage, as is
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. Furthermore, we develop advanced scattering methods and machine learning tools for data analysis. For more information, see www.soft-matter.uni-tuebingen.de Qualification and skills Candidates should have good
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or integrated pest management with hands-on experience in agricultural field trials solid knowledge of statistical analysis and publication of research results first experience in acquiring third-party funding is
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PostDoc in "Geopolitical dilemmas for management: transfer of governance for the Southern Ocean" ...
interdisciplinary experience has been gained (i.e., Ecology, Biology, Oceanography) Strong skills and evidenced experience in textual analysis (i.e., policy or discourse analysis) Knowledge of the marine social
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Postdoc in "Navigating uncertainty: Planning marine protected areas in a changing Southern Ocean"...
statistics and the ability to apply quantitative analysis to ecological data A strong background in programming (preferably in R), including data manipulation, statistical analysis, and spatial modelling and
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discovery, scientific programming and genetic analysis. We encourage applications also from candidates with little background in biology or medicine, and a keen interest to learn. Recent publications: Clarke
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cutting-edge big/deep data analysis methods, including machine learning and artificial intelligence. The ideal candidate will therefore have a strong background in data science and in the application and
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or a related discipline A solid background in climate and atmospheric sciences, and extreme weather ideally supported by knowledge of machine learning and time series analysis is of advantage, as is