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University degree in data science, computer science, information science, computational ecology, statistics, or equivalent Competence in Python, R or other relevant programming languages (knowledge of LabView
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of the theoretical foundations of economics, as well as relevant empirical and experimental methods • Experience in data analysis using statistical programs such as Stata or R • Enthusiasm for research and teaching
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the research department is English); Good knowledge of German, Arabic, Russian, and/or Chinese is a big plus; Training in and experience with statistical methods, advanced regression models, and excellent R
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interact in the Center for Behavioral Brain Sciences (www.cbbs.eu). Collaboration with the Central German site of the German Center for Mental Health Halle-Jena-Magdeburg (www.c-i-r-c.de) is possible
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chromatography is required. Additionally, familiarity with precursor and reporter ion quantification & PTM analysis tools, and experience in programming languages like R and/or Python would be essential
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as a student at a German university You have strong Excel skills, and ideally, experience in programming with Python or R. You are organized, reliable, and proactive You are a good communicator and
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, preferably using R Experience with sea-going expeditions on research vessels and sampling of plankton Willingness to participate in interdisciplinary work Good communication skills in order to work in a highly
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Python, R, and familiarity with bioinformatics tools and databases. Excellent communication skills, with the ability to collaborate effectively across multidisciplinary teams. WE OFFER: Located in a region
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Bayesian belief networks; Experience in scenario development approaches, e.g. SSPs; Experience in the application of R-based analytical tools for qualitative or semi-quantitative modelling, incl. RQDA
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Max Planck Institute of Immunobiology and Epigenetics, Freiburg | Freiburg im Breisgau, Baden W rttemberg | Germany | 3 months ago
pipelines. Expertise in machine learning, with a particular emphasis on the application of large language models (LLMs) in biological data analysis. Proficiency in programming languages such as Python, R, and