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electron microscopy (TEM). Interest and experience in working with industrial problems. Experience/ knowledge within electrochemistry. Experience with programming and/or data processing in Python. Good oral
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laboratory work. Experience with molecular biology techniques, such as RNA sequencing (from RNA extraction to data analysis) Experience with immunohistochemistry Experience in using R, python or similar
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intelligence, machine learning, statistical estimation methods, software tools, and big-data frameworks. Programming languages such as e.g. Python, C++, and LABVIEW. Emission control rules and regulations in
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Python) Mathematics Knowledge of these needs to be documented, and GPA (grade point average) and translation rules for the European Standardized Character System must follow the application. Moreover
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microfabrication techniques, such as photolithography and etching. Experience with programming and/or data processing in Python. Knowledge about solid state physics. Knowledge about magnetic materials. Personal
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and/or data processing in Python. Knowledge about solid state physics. Knowledge about magnetic materials. Personal characteristics To complete a doctoral degree (PhD), it is important that you are able
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imperative, both orally and written. Documented experience with scientific programming (e.g. Python, Matlab, R; any history of activity on GitHub) as well as computational or statistical methods for data
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selection criteria Strong skills in relevant programming languages, particularly Python and C++, good knowledge in ROS (Robot Operating System) is an advantage, and best practice in data management and use
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selection criteria Strong skills in relevant programming languages, particularly Python and C++, good knowledge in ROS (Robot Operating System) is an advantage, and best practice in data management and use
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, Atmospheric Science, Environmental Science, or related fields Good knowledge and skills in statistics and programming (e.g. R or Python) is required Experience with data analysis related to terrestrial ecology