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innovation and active participation. For TUD diversity is an essential feature and a quality criterion of an excellent university. Accordingly, we welcome all applicants who would like to commit themselves
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, memristive devices), and the evaluation with e.g. machine learning and image processing benchmarks Requirements: excellent university degree (master or comparable) in computer engineering or electrical
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reuse of energy systems analysis processes. In line with FAIR and Linked Open Data principles, you will design interfaces that enable the smooth processing of big data in the context of scientific, AI
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the economics of innovation or digital transformation. Our team is dedicated to exploring the effects of innovation and digital transformation on the economy and society, focusing on how the state can design
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generating a high-quality training dataset to support the development of the AI foundation model Contributing to the design and implementation of advanced deep learning architectures (e.g., Transformers, CNNs
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of embedded machine learning, neuromorphic hardware and deep learning accelerators. Want to get more information? Click here. What you will do Design analog and mixed-signal circuits, such as data converters
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Your Job: This position focuses on building, operating, and testing superconducting quantum devices. Your tasks in detail are: Design and fabrication of superconducting quantum circuits Setting up
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Your Job: One essential step towards the ramp-up is the identification of site-specific optimal design of DACS plants, which will be the focus of the advertised PhD. To identify optimal DACS plant
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for the modeling and simulation of 3D reconfigurable architectures e.g. based on emerging technologies (e.g. RFETs, memristive devices), and the evaluation with e.g. machine learning and image processing benchmarks
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for a PhD. The at the Institute for Software and Systems Engineering (ISSE) located Research Group Digitized Green Tech focusses on the design and the development of digital solutions to shape a