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., Python, MATLAB, R, C++, FORTRAN) is required Ability to actively communicate and co-operate within a larger research team is required. Experience with LINUX environments and analysing large datasets from
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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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., Python, Matlab, R) is required. Knowledge of climate variability and predictability is an advantage. Experience with Linux clusters, and running Earth System Models, is an advantage. Experience with
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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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. 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
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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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with the North Sea or South Atlantic salt basins is an advantage. Experience of programming (Python, Matlab, Fortran) is an advantage. Applicants must be able to work independently and in a structured
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modelling. Applicants must have good skills in programming (e.g. Python, R, Java Script) Experience (for example a master project or internship) working with snow or the cryosphere is a requirement