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Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung | Oldenburg Oldenburg, Niedersachsen | Germany | 10 days ago
of Oldenburg Your Profile PhD in marine ecology, finalized by the start of the project Advanced statistical modeling skills including analysis of biodiversity time series and functional traits, evidenced by
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Excellent command of advanced statistical methods, such as network analyses, using the R programming language Strong publication record relative to the career stage, demonstrating research excellence and
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with R, statistical and spatial analysis Excellent communication and teamwork skills Excellent organizational skills Experience with field work in post-disturbance forest conditions (desired) Experience
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-scale biological datasets derived from both the host and the microbiome, employing advanced statistical methods and cutting-edge artificial intelligence techniques to uncover novel insights
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The project will require coding for data analysis and statistics, as well as NGS data analysis. Experience with either of these would be advantageous but an eagerness and commitment to learn is more important
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corresponding scientific project management is desirable Confident in independent bioinformatic and statistical analysis of high-throughput sequencing data Experience in working with biofilms is desirable
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Familiarity with statistical analysis and interpretation of experimental data Experience in scientific writing, especially for publications and third-party funding applications Proficient English and, ideally
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PhD or equivalent qualification in computer science, statistics, mathematics, physics, and/or engineering, or a degree in biological science with demonstrated experience in computational and statistical
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Max Planck Institute for Brain Research, Frankfurt am Main | Frankfurt am Main, Hessen | Germany | about 1 month ago
A doctoral degree in neuroscience or a related STEM field Prior experience in systems neuroscience using animal models A solid foundation in quantitative data analysis and statistics Programming
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Identification of soil invertebrates (e.g. mites, springtails, insects) using modern and classical techniques Laboratory analyses of soil properties Statistical analysis of complex ecological datasets Presentation