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hydrogen storage to maximize energy efficiency while keeping the grid reliable and secure. Our research method is engineering-oriented, prototype-driven, and highly interdisciplinary. Our typical research
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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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processes in inflammatory contexts Planning and carrying out own independent research projects Planning and independent execution of experiments Independent data processing and evaluation Supervision
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for the applications of the production, which are taken in our industry projects directly on site into the operation. What you will do Creation and preparation of image and tabular data in collaboration with experts
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on ranges from concept and prototype development for industrial laser manufacturers to publicly funded projects in the field of basic research, for example in the generation of EUV radiation through non
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System analysis, prognosis and control Transport processes Image Processing High Performance Computing Financial Mathematics Materials characterization and testing What you bring to the table You are
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System analysis, prognosis and control Transport processes Image Processing High Performance Computing Financial Mathematics Materials characterization and testing What you bring to the table You are
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to maximize energy efficiency while keeping the grid reliable and secure. Our research method is engineering-oriented, prototype-driven, and highly interdisciplinary. Our typical research process includes
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an overall picture of future mobility together with the project partners. Your Profile You have a strong interest in automated driving and mobility transition. You have completed your master's degree in a
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channels, going beyond the Shannon paradigm, which offers many exciting open questions to work on. Thirdly, the project aims at investigating non-Shannon-type inequalities for the quantum entropy, which in