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datasets to specialised colleagues. Experience with large datasets, statistical analysis, and programming in R is considered an asset; A flexible attitude towards working hours, for example in relation
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quantitative MEL (monitoring, evaluating and learning) methods. Proficiency in R is considered a plus, A proven ability to acquire, lead and deliver projects for private sector clients and maintain strong client
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that you have to work with large datasets, from i.e. semi-quantitative LC-MS/MS proteomics, therefore proven affinity with R is an asset. You will work here The research is embedded within the chair
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systems. Proven programming skills in Python, R, or a comparable language. Interest in developing methodologies to assess localized climate hazards, exposure, and vulnerability as inputs to impact-based
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(or strong willingness to learn) in programming and data analysis (e.g. Python, MATLAB, R, Fortran, or similar). Curiosity and motivation to work on fire emissions, air quality, and climate questions. Ability
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(agent-based modeling, differential equations) or machine learning tools. Good programming skills in one of the following programming languages: R, Python, MATLAB, or similar; Excellent English language