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comprehensive study on the flexibility of electrical distribution grids, evaluating various scenarios and their impacts Design and further develop geo-referenced synthetic distribution grids generation tool
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- 3.4 years Further development of your personal strengths, e.g. through an extensive range of training courses; a structured program of continuing education and networking opportunities specifically
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now and become part of this innovative research team! Your task is to develop innovative processes for releasing hydrogen from LOHC molecules. In addition to conventional dehydrogenation, you will
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of training courses; a structured program of continuing education and networking opportunities specifically for doctoral researchers via JuDocS, the Jülich Center for Doctoral Researchers and Supervisors: https
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dataset for fast finger motion Use the dataset to train an artificial neural network for finger-position estimation Making a live demonstration of finger-position estimation with electromyographic signals
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for Energy Materials” in cooperation with partners from academia and industry from several European countries. Your tasks in detail: Conduct cutting-edge research to develop and validate advanced AI
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hydrogen energy sector. Your Job: Conduct cutting-edge research to develop and validate advanced AI methodologies for the characterization, modeling, and simulation of energy materials. Develop code and
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expertise in engineering, data analytics, and artificial intelligence. Develop and synergize metadata and ontologies, crafting a first-generation recommendation model for a metadata marketplace, enhancing
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, or algorithms to integrate neuromorphic-inspired computing paradigms. Your main tasks will include: Identify areas where neuromorphic-inspired paradigms can be applied Develop concepts to integrate CMOS circuits
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PEM electrolysis. To this end, you will examine in-depth technical and economic factors. In the second part of your thesis, you will develop a detailed techno-economic electrolyzer model based