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optimization lab (EES EMPDO lab). The former focuses on intelligent energy network research, including: demand management and flexibility, digital twinning, data analytics, smart grid ICT architectures and
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will investigate novel frameworks to accelerate SRS in HPC environments. The PhD candidate will work at the Ship Hydrodynamics section of the Department of Maritime and Transport Technology (Faculty
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energy network research, including: demand management and flexibility, digital twinning, data analytics, smart grid ICT architectures and systems integration in multi energy systems. The latter specializes
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on intelligent energy network research, including: demand management and flexibility, digital twinning, data analytics, smart grid ICT architectures and systems integration in multi energy systems. The latter
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conferences; Actively participating and contributing to the PhD community of Fertile Soils and the Landscape Architecture and Spatial Planning cluster. You will work here The research is embedded within
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, this PhD will explore machine-learning (ML) methods to significantly reduce the turnaround time of SRS, thus enabling their use for industrial design processes. By combining state-of-the-art numerical
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We are seeking a highly motivated PhD candidate to join our research team in the field of mixed-signal IC design, focusing on the implementation of physics-based computing paradigm. The ideal
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About the project and group This position is funded within the context of the “Future Network Services: 6G” project. A unique Dutch alliance, comprising 60 leading ICT businesses, mobile operators
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Technology Eindhoven (CWTe). All PhD projects within Polaris are strongly connected to the industrial partners. Information In the rapidly evolving field of wireless communication and radar systems, the demand
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simulate ultra-low-power energy-harvesting and power-management ICs using CMOS technologies. Develop novel rectifier and MPPT architectures optimized for mechanical energy sources. Implement, tape out, and