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the project/work tasks: Advanced data management on large datasets to facilitate data for statistical analyses Design and plan analyses Make efficient analysis pipe-lines in the statistical software R
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datasets to facilitate data for statistical analyses Design and plan analyses Make efficient analysis pipe-lines in the statistical software R for automatic statiscal analyses of a large number of
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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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mathematical modelling tools. Excellent knowledge of programming languages such as R, Python, Julia, etc. Familiarity with AI algorithms and Machine Learning Fluent oral and written communication skills in
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the link “Apply for this job”. The following documentation must be uploaded: official transcripts and diplomas master's thesis/major thesis certificates scientific work and R&D activities, as well as a list
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estimators, or machine learning) or other advanced statistical modelling. Advanced programming skills in Stata, R, Python or a similar software. Strong academic background with publications in international
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, or a closely related field. Proficiency in analysing large climate and environmental datasets using statistical or programming tools (e.g., Python, R, MATLAB). Capability of both managing research
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., Bash, R, Python) for data processing, statistical analysis, and bioinformatics workflows. Experience working in high-performance computing environments is an advantage. • Field or laboratory
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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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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