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and evaluation of innovative data- and machine learning-based systems to integrate more renewable energy into our energy systems and make energy use more efficient. We develop new optimization methods
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team and actively participate in the DIPONI project (“Digital Transformation in Polymer Processing: Interoperability and Machine Learning Solutions for Process Optimization and Sustainability
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on these considerations, solutions will be developed and implemented to create an advanced testing platform for the comprehensive evaluation of the long-term stability of invasive brain-computer interfaces. Your task will
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of study. You have knowledge of artificial intelligence and its application in the analysis of company data. You have experience with Generative AI technologies (e. g. GPT models, machine learning). You are
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transfer of theoretical concepts into real-world applications You have gained practical experience in production engineering A high level of motivation, willingness to learn, and analytical thinking A high
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optical communication networks and systems, as well as machine learning, computer vision and compressing digital videos. Become a part of our team and join us on our journey of research and innovation! What
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and evaluation of innovative data- and machine learning-based systems to integrate more renewable energy into our energy systems and make energy use more efficient. We develop new optimization methods
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existing technologies, right through to the tested prototype. The Data-based Methods team at Fraunhofer ENAS develops real-world applications using AI, machine learning and computer vision. The main focus is
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applied electroacoustics and audio engineering, AI-based signal analysis and machine learning, and data privacy and security. At the headquarters, on the campus of “Technische Universität Ilmenau
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applied electroacoustics and audio engineering, AI-based signal analysis and machine learning, and data privacy and security. At the headquarters, on the campus of “Technische Universität Ilmenau