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At the Faculty of Engineering and Science, Department of Materials and Production a position as PhD stipend in Muscle Neuromechanics and Ultrasound Imaging, within the doctoral programme Materials
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program with research visits, partner universities, and visiting lecturers, the graduate school actively supports forming a strong multi-disciplinary and international professional network between PhD
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:100% of the full-time weekly hours Tasks: The PhD student will be responsible for the modeling and simulation of 3D reconfigurable architectures e.g. based on emerging technologies (e.g. RFETs
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therefore teams up materialists, electrical engineers, and computer scientists of TUD, RWTH Aachen and Gesellschaft für Angewandte Mikro- und Optoelektronik mbH ( AMO ) in Aachen, Forschungszentrum Jülich
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spin-photon entanglement. With this milestone demonstration, we strive to kickstart subsequent developments towards a quantum internet architecture. The objective of this PhD thesis is to demonstrate
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At the Faculty of Engineering and Science, AAU Energy, a position as PhD stipend is available within the general study program. The PhD stipend is open for appointment from September 1st. 2025
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Leibniz Institute of Ecological Urban and Regional Development (IOER) • | Dresden, Sachsen | Germany | 40 minutes ago
semester in EUR None Combined Master's degree / PhD programme No Joint degree / double degree programme No Description/content The Dresden Leibniz Graduate School (DLGS) is a joint interdisciplinary facility
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PhD Studentship in the History of Architectural Representations This call is for a PhD student that is interested in exploring the history of architectural representations. Topics of any time
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or infrastructure. This is what makes our daily work so meaningful and exciting. The Division of Computational Genomics and Systems Genetics is seeking from October 2025 a PhD Student in Deep Learning for Rare
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., StableDiffusion) and large language models (LLMs) based on the transformer architecture [6] (e.g., ChatGPT). In general, the above generative models need considerable amount of computational resources in terms