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analysis of large data sets, statistical modeling, and knowledge of at least one programming language (e. g.: R, Python and/or Julia) are required. Experience in machine learning and image recognition
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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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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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skills in one or more languages (Python, C/C++, or others) experience in mechanical testing profound knowledge of machine learning methods (e.g., neural networks, Gaussian processes, active learning
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for data analysis and experiment automation (Python preferred) Excellent English communication skills (written and verbal) Demonstrated ability to work in interdisciplinary and collaborative environments
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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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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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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
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field of study Interest in energy technology and energy economics Experience in energy system modelling is an advantage Basic programming skills, ideally in Python Independent and analytical way
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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