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Field
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engineering, data science, or related fields Strong programming skills (especially in Python), and experience with simulation, modelling, data analysis, machine learning, and hardware control Solid
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documents, including OCR post-processing and parsing of legacy texts Proficiency in scientific programming (preferably Python), version control (e.g. Git), and data standards such as RDF and Darwin Core
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mathematics, computational biology, quantitative biology, or a related field. Experience in ABM development and ODE/PDE modeling and analysis. Strong programming skills (Python, Julia, Matlab, C++, or similar
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Programming skills in Python, R, and/or GIS tools Highly valued: Background in LiDAR point-cloud analysis and vegetation structure analysis or habitat monitoring Experience applying AI or machine learning
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Programming skills in Python, R, and/or GIS tools Highly valued: Background in LiDAR point-cloud analysis and vegetation structure analysis or habitat monitoring Experience applying AI or machine learning
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Python for scripting and data analysis, metabolite ID via MS/MS and annotation (e.g. SIRIUS, HMDB, authentic libraries etc.), statistical uni- and multivariate analysis, data visualization (PCA score
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. The required expertise includes raw UPLC-MS-collected data preprocessing with XCMS, MZmine or MSDIAL, normalization procedures, proficiency in R and/or Python for scripting and data analysis, metabolite ID via
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or epigenetics datasets, Strong skills in R programming, Linux shell scripting and Python or another relevant scripting language, Excellent written and spoken English skills. The following will be considered
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, power electronics, and system protection. Strong programming skills (e.g., Python, C/C++, Julia) Researcher III (all above qualifications for Researcher II, plus): Demonstrated leadership in one or more
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Carl von Ossietzky Universität Oldenburg | Oldenburg Oldenburg, Niedersachsen | Germany | 3 months ago
team spirit Good communication skills Experience programming in python Experience in computational modeling of neural circuits and in the mathematical analysis of neural computations Research experience