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a focus in economics, or related disciplines strong analytical and methodological skills with a focus on quantitative data analysis (e.g., econometrics, statistics, machine learning) a high motivation
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and simulation tools. Research topics include geometric modeling of engineering products, methods of geometric analysis, methods of Building Information Modeling, modeling and simulation of construction
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the testing of newly devel-oped materials and the use of machine learning methods to process complex data sets. The focus is on techniques such as ultrasound, radar, computed tomography, acoustic emission
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the perspective towards generating data for entrepreneurial seed funding (GO-Bio etc.) for a further development of the technology towards the market. In that sense we also highly encourage candidates that would be
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the objectives more precise; working on the individual PhD study project with its focus on the methodological contributions as well as on empirical data processing for the case study analysis in collaboration with
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, environmental or natural resource economics) or related disciplines strong analytical (i.e. microeconomics, production or resource economics) and methodological skills with a focus on quantitative data analysis
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position is part of a large cooperation project with partners from industry and academia. The candidate will measure and model data on the reaction kinetics and mass transfer in reactive chemical systems. A
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and ability to express yourself in spoken and written German and English language • Proficient use of common programming languages, MS-office, data storage, and image processing • Ability to support the
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• Very good communication skills and ability to express yourself in spoken and written German and English language • Proficient use of common programming languages, MS-office, data storages and image
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are therefore particularly encouraged to apply. To apply, email a motivation letter, CV, and contact information for two references to Dominik Bucher (Dominik.Bucher@tum.de). More details on the previous