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landscapes using both proprietary and publicly available data sources Strong background in data analysis, preferably, proficiency with tools such as R. Experience with AI/ML-based approaches for data analysis
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mammalian cell culture is required Documented knowledge in bioinformatics and programming (Python, R) is required Experience in LC-MS and mass spectrometry is required Experience from relevant research
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biology, molecular biology including mammalian cell culture is required Documented knowledge in bioinformatics and programming (Python, R) is required Experience in LC-MS and mass spectrometry is required
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bioinformatics, especially Python and/or R are required Experience from relevant research projects investigating cellular metabolism, and/or protein modifications and signalling, respectively, will be considered
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biochemistry are required Profound knowledge in bioinformatics, especially Python and/or R are required Experience from relevant research projects investigating cellular metabolism, and/or protein modifications
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, and python/Matlab/R or similar languages. Experience with “traditional” climate modelling, data-driven climate modelling, and working with large ensembles of climate/weather model output are advantages
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); mapping of protein interactions; RNA mapping via in-situ sequencing; spatial metabolomics; RNA sequencing; as well as bioinformatics skills (e.g., R) for digital image analysis and advanced statistical
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well as experience in atmospheric dynamics or climate dynamics, basic shell scripting, and python/Matlab/R or similar languages. Experience with “traditional” climate modelling, data-driven climate modelling, and
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the master's degree has been awarded. The candidate must have good knowledge in atmospheric dynamics. Proficiency in scientific coding and data analysis (e.g., Python, MATLAB, R, C++, FORTRAN) is required
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cycle processes, dynamics of oxygen and nutrient cycles, is required. Expertise in scientific scripting, programming, and data analysis (e.g., Python, Matlab, R) is required. Knowledge of climate