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and methodological skills with a focus on quantitative data analysis (e.g., econometrics, statistics, machine learning) a high motivation and the ability to work independently with a strong team
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are being developed that provide AI-supported tools to identify suitable sources and optimize utilization decisions throughout the product life cycle. Various machine learning approaches are to be used
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These are positions for Doctoral Students, based in Tübingen in an interdisciplinary research group working at the interface of Machine Learning, Medicine, and Biology. Doctoral Students will engage
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, agricultural sciences with 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
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analysis (e.g., econometrics, statistics, machine learning) A high motivation and the ability to work independently with a strong team orientation Excellent spoken and written English and the will
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, agricultural sciences with a focus in economics, or related disciplines - strong analytical and methodological skills with a focus on quantitative data analysis (e.g., econometrics, sta-tistics, machine learning
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analytical and methodological skills with a focus on quantitative data analysis (e.g., econometrics, statistics, machine learning) a high motivation and the ability to work independently with a strong team
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Your Job: In this position, you will be an active part of our "Simulation and Data Lab Applied Machine Learning". Within national and European projects, you will drive the development of cutting
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Lehrstuhl für Nachhaltige Thermoprozesstechnik und Institut für Industrieofenbau und Wärmetechnik | Aachen, Nordrhein Westfalen | Germany | about 6 hours ago
. Methodological knowledge in the field of machine learning is an advantage. You have a high level of independence and commitment. You would like to develop and realise your own ideas. You enjoy working in a team
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the use of machine learning methods to process complex data sets. The focus is on techniques such as ultrasound, radar, computed tomography, acoustic emission analysis, and infrared thermography