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background in programming (Matlab, python, …) familiar with Multi-body dynamic tools good knowledge of statistics familiar with signal processing, operational modal analysis Personal characteristics Strong
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languages (e.g. FORTRAN, Python) is required. A strong background and experience in operating, analysing and visualising large datasets is desired. Track record of peer reviewed publications in high level
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dynamics or climate dynamics, basic shell scripting, and python/Matlab/R or similar languages. Experience with “traditional” climate modelling, data-driven climate modelling, and working with large ensembles
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analysis is a requirement Experience in using relevant software to perform complex tasks, e.g. R, ArcGIS, and Python is a requirement Experience in the mapping and modelling of ecosystem services is an
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requirement Experience in using relevant software to perform complex tasks, e.g. R, ArcGIS, and Python is a requirement Experience in the mapping and modelling of ecosystem services is an advantage Knowledge
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background in statistics is required, as well as experience in atmospheric dynamics or climate dynamics, basic shell scripting, and python/Matlab/R or similar languages. Experience with “traditional” climate
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distribution modelling Experience with spatial analysis and mapping tools (e.g., QGIS, ArcGIS, or spatial packages in R/Python) Interest or experience in applying AI or machine learning methods to ecological
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) Documented record of advanced quantitative methods skills in R and Python, specifically Experience with GIS and spatial data analysis Experience with natural language processing or text-as-data approaches
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dynamics, numerical modeling, and scientific programming is required. The following areas of expertise are considered beneficial: Experience in scientific computations using Python, C, C++. Experience in
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. Proficiency with modern data analysis tools such as programming languages R, or Python. Mass cultivation of algae and/or scaled up bioprocess engineering which could include fermentation or biomass harvesting