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models combining machine learning, and physics-of-failure (PoF) approaches using in-situ data • You work on projects independently • You will present your work at international conferences and
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, energy conversion, machines, power quality, and distribution Experience in designing and integrating electrotechnical test benches Proficiency in microcontroller architectures (STM32, ESP32, Arduino, etc
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control engineering, optimization algorithms Control of drones and flight experiments as well as knowledge in AI / Machine Learning would be an asset Outstanding academic records Teamworking experience, e.g
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of CLiPS, which focuses on the application of statistical and machine learning methods, trained on corpus data, to explain human language acquisition and processing data, and to develop automatic text
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. You have a good knowledge of Python and machine learning. You have an excellent knowledge of English. Your research qualities are in line with the faculty and university research policies . You act with
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and building and maintaining machines and automation, preferentially with experience in plant biology. Job description Maintenance of automated phenotyping systems, containing conveyer belts or gripper
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of Applied Mathematics: Statistics Position You will work actively on the preparation of a PhD thesis in the field of statistics and machine learning. You will publish scientific articles related
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. Assist in stock management, data management, and the QC program of the facility. Train the users on the analyzers and FACS machines. Assist researchers with acquiring, analyzing, and presenting their data
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experience with scientific computing, data analysis, machine learning and/or AI You have an interest in environmental sustainability and pharmaceutical production Considered a plus: You have experience with
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background in machine learning, including Natural Language Processing. You have excellent coding skills in Python; hands-on experience in deep learning frameworks such as PyTorch or Tensorflow is a plus You