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++, Python, and JavaScript languages, multi- and many-core SoC, RISC-V, hardware synthesis, hardware-software co-design, (meta-heuristic) optimization algorithms, machine learning frameworks, (bonus topics
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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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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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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, statistics, machine learning) a
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knowledge of machine learning (e.g., in the areas of object detection and identification, generative AI, etc.) Good written and spoken English skills (min. level B2) Good written and spoken German skills (min
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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