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and library preparation is required. The applicant must have strong independent bioinformatics and programming skills in R, Python or equivalent. The applicant must be able to perform end-to-end
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knowledge of mountain environmental processes, alpine ecology, and/or vegetation change; experience from or competence in using R, Python or comparable programming and analytical tools; show evidence of being
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is a requirement. Such experience may have been obtained through academic coursework, research projects, or professional employment. Experience with scientific programming using Python, R, Matlab
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quantitative skills are required. Experience and/or a strong interest in meteorology is an advantage. Demonstrated proficiency with scientific programming (e.g. Python) is an advantage. Demonstrated proficiency
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events and in machine learning for the earth system is required Strong and demonstrated programming skills are required Prior experience with geospatial data analysis in Python, working on scientific HPC
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. Demonstrated proficiency with scientific programming (e.g. Python) is an advantage. Demonstrated proficiency in geospatial data analysis is an advantage. Applicants must be able to work independently and in a
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the master's degree has been awarded Solid background in mathematics and physics is a requirement Experience in scientific programming (e.g., Matlab, Python) is requirement Experience in statistical analysis
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condition of employment that the master's degree has been awarded. Experience with Python programming, the ability to work comfortably in the Unix/Linux environment, and handling large climate datasets in
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existing modules (by then) developed by the project team of ‘OceanCoupling ’. Develop code scripts using programming languages such as Fortran, Python, and/or MATLAB Validate and test of customized scripts
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with programming in Python is a requirement Experience with telecentric particle imagers, image analysis, and machine learning for particle recognition is an advantage Experience of working with wave