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if applicants have completed courses that cover these topics during their studies Good programming skills (for example Python, Java or JavaScript) and software engineering practices is a requirement. Familiarity
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during their studies Good programming skills (for example Python, Java or JavaScript) and software engineering practices is a requirement. Familiarity with real-world programming language specifications
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skills in one or more languages (e.g., Python, MATLAB, Fortran, C++) and must demonstrate their proficiency. Strong analytical skills and capabilities in data processing and mathematical modelling is a
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deadline. It is a condition of employment that the master's degree has been awarded. Applicants must have strong programming skills in one or more languages (e.g., Python, MATLAB, Fortran, C++) and must
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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
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is also expected to re-implement historical narrative systems in Python and help determine the course of a larger collaborative CNS project dealing with such systems. About the LEAD AI fellowship
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UNIX/Linux interface and basic programming (e.g. Python) is a requirement. Experience with machine learning is an advantage. Experience from free energy calculations is an advantage. Applicants must be
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. Experience in scientific programming (e.g., Matlab and Python) is a requirement. Experience with analysis of climate data sets is an advantage. Applicants must be able to work independently and in a structured
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using Python, R, Matlab, Julia or similar is required. Knowledge of energy systems, energy system modelling or the European energy market will be an advantage. Understanding of atmospheric processes