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Field
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-magnet design and hardware. Experience with numerical simulation of plasma accelerators (particle-in-cell simulations) and/or particle tracking. Programming skills in Python, MATLAB and/or C++ at a
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functional theory or related techniques Experience with data analysis using, e.g., Origin, Python or MatLab Programming skills, e.g. proficient with Labview or Python Language requirement: Good oral and
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Documented experience in scientific programming (e.g., Python, or similar) Excellent written and oral English skills PLEASE NOTE: For detailed information about what the application must contain, see paragraph
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modelling, programming, systems thinking, and qualitative/quantitative research methods Documented programming experience for example GitHub project on Python, Julia, JavaScript and cloud computing platforms
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for example GitHub project on Python, Julia, JavaScript and cloud computing platforms Possesses a strong academic record, with relevant experience in either industry or academia. Has prior professional
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, educational, or demographical outcomes. Familiarity with R, Python, Julia, or other relevant computing languages. Experience with register data or other types of big data. Training in application of genetic
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. Good knowledge of the topic of Cryospheric Processes is a requirement Proficiency in scientific coding and data analysis programming languages, such as Python or MATLAB, is a requirement. Experience with
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to the application deadline. It is a condition of employment that the master's degree has been awarded. Solid background in mathematics and physics is a requirement. Experience in Fortran, Python, or in a similar
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. Applicants must be proficient in both written and oral English Advantages: Documented education or work experience in the following areas: Numerical modelling in acoustics Programming in Python and MATLAB
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. Familiarity with R, Python, Julia, or other relevant computing languages. Experience with register data or other types of big data. Training in application of genetic data. Experience with multilevel modelling