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until the positions are filled. Contact: Dr. ir. Gerben R. Stouten Environmental Biotechnology, Department of Geosciences, University of Tübingen
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RNA sequencing workflows and basic bioinformatics • Experience with Python and R for transcriptomic data analysis We offer The position (TV-L13 (65%) salary according to German public sector regulations
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temperature and water content Experience and expertise in database management and software automation Experience with statistical analysis of experimental data, preferably in R Excellent English language skills
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of the southern Baltic Sea Experience in (pre-)cultivation of macroalgae (preferably Fucus vesiculosus and Furcellaria lumbricalis) Experience with statistical analysis of experimental data, preferably in R
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of complex measurement data (e.g.,Python/R/MATLAB or comparable analysis environments) and structured documentation Good German and English language skills, written and spoken Willingness to travel Willingness
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-envbiotechspam prevention@ifg.uni-tuebingen.de . Applications are reviewed until the positions are filled. Contact: Dr. ir. Gerben R. Stouten Environmental Biotechnology, Department of Geosciences, University
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-domain context. Good knowledge of programming languages (e.g. Python, R, Java, C#, C++) Good knowledge of object orientation and at least basic knowledge of UML Knowledge in the field of machine learning
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Helmholtz-Zentrum Dresden-Rossendorf - HZDR - Helmholtz Association | Freiberg, Sachsen | Germany | 4 days ago
rigor # Proficiency in Python (or Julia/R) for data handling, ML model development, and statistical analysis # Ready to work with time‑series data, sensor fusion, and feature engineering # Very good
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://umg.recruiting-portal.com/r/z01o6dybsgn7kn8/PhD+student+position+fmd/37… Requirements Research FieldAllEducation LevelMaster Degree or equivalent Skills/Qualifications Your qualifications completed Master of
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of potential targets to delay vertebrate brain aging. Your Tasks: Performing bioinformatic analyses in R (including packages such as R/qtl) using existing genomic, transcriptomic, and proteomic datasets Applying