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, preferably using MATLAB and/or Python. Good written and spoken English. Applicants not exempt from NOKUT requirements must document English proficiency (TOEFL or IELTS). TOEFL - Test of English as a Foreign
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, e.g. in Python, particularly for machine learning Experience with machine learning theory, evaluation metrics, algorithmic fairness, statistics, or optimization is an advantage Language requirement
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listed in the project description above (ideally SAR for cryosphere applications) Strong programming skills (preferably Python or MATLAB) Strong background in statistics Fulfillment of the requirements
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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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. • Programming or scripting skills (e.g., R, Python, bash). • Excellent written and verbal communication ability in English. English requirements for applicants from outside of EU/EEA countries and exemptions
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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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/optimization/programming software (e.g., HOMER, GAMS, and Python). Evidence of previous scientific writing or academic publications (e.g., peer-reviewed journals), industrial collaboration, knowledge transfer
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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