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analysis and analytical data analysis workflows, together with other team members Implementing AI-based microscopy image analysis software as python packages Developing algorithms to deploy machine learning
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experiences in working with remote sensing data, climate data and programming skills (R or Python) are desired. You enjoy working in an international team and you are keen on developing a key set of research
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subject areas. Both working independently and working in a team, e.g. during the measurement campaigns, is particularly demanding. Knowledge of programming languages such as Python is an advantage
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themselves with new subject areas. Both working independently and working in a team, e.g. during the measurement campaigns, is particularly demanding. Knowledge of programming languages such as Python is an
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of the (computational) mechanics of solids and the finite element method and/or spectral solvers Practical experience in at least one programming language (preferably Python) and experience with the use of Unix/Linux
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to submit the dissertation after 3 years and 9 months of research. Desired requirements specific to this project include: experience with a range of relevant computer programming languages such as Python, R
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programming background with expierence in using Python, matlab, and/or Java, etc. a good command of German and English, both for teaching and for the preparation of research proposals and publications process
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problems Proficiency in data analysis and programming using at least one statistical program such as R, Python, or similar programming languages Experience with GAMS, GTAP, and Exiobase is an asset. Skills
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data. You bring first experience with biostatistics methods, e.g. with mixed-models. You are familiar with data analysis using programming languages like R, and/or Python. You have excellent
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system modeling is beneficial but not mandatory First programming skills, ideally in Python Independent and analytical way of working Reliable and conscientious working style Fluent written and spoken