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federated learning for decentralized AI model training for quality assurance of machining processes within the project »FL.IN.NRW «. A custom dataset composed of machine internal signals and external sensor
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). Knowledge of Docker and machine learning is considered a plus. Knowledge of standard bioinformatics tools for analyzing and interpreting Next Generation Sequencing data. Excellent oral and written
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necessary records and entering data onto computer systems. Your role: Animal husbandry, care and use Provide day to day routine husbandry, maintenance and care of LAR fish colonies (zebrafish, medaka
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Biology, Computer Science or related studies) Experience in Python with PyTorch (or equivalent) programming Experience in sequencing data analysis Basic knowledge in machine learning Experience with linux
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: machine learning, data analysis, energy technology Experience with common deep learning and data analysis frameworks (e.g., PyTorch, Numpy, Pandas, sklearn, etc.) Independent, structured, and reliable way
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of research focus include machine learning/learning analytics, multimodal assessment, adaptive learning in online settings, and the role of self-regulation in learning with AI. Close networking with
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pursuing a Bachelors or Masters degree in engineering, physics, mathematics or computer sciences and related discipline and/or an unaffiliated recent graduate with a Bachelor/Master degree from
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• Experience with machine learning frameworks (e. g. TensorFlow, PyTorch) and Explainable AI (XAI) • Experience with machine learning and/or AI-based methods for data analysis • Experience in processing and
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regulations. Furthermore, the gathered data serves as a valuable resource for machine learning applications, enabling predictive analytics and facilitating continuous improvement in coating processes through
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Quality”, we focus on data-driven optimization of production processes with the help of machine learning and artificial intelligence. Laser processes enable highly precise and flexible material processing