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Field
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make extensive use of low-fidelity simulations which can provide fast but inaccurate solutions depending on the flow complexity. To close this gap, this PhD will explore machine-learning (ML) methods
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for spatial and reconfigurable computing for HPC, post-Moore architectures, and sustainability in modern computing systems. The MCS group has a central role in organizing the national and international computer
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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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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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The PhD position is part the prestigious POLARIS (Pathway towards Opportunities for Large scale Applications of Radically Integrated Systems) project. Polaris is a large flagship program (funded by
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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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Job description We are looking for an excellent and motivated PhD candidate to join the Microelectronics Department at TU Delft, focusing on the design of innovative power management integrated
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group, at TU Delft to pioneer self-organizing edge infrastructure that will define the next generation of Internet architecture. This PhD position offers you the opportunity to shape the future
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this PhD project, you will investigate the co-design between event-based learning algorithms and neuronal hardware units with multi-scale time constants. The algorithmic methodology will exploit recent
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longer sustainable. This project pioneers a new paradigm: we design smart, low-power digital AI co-processors that learn and correct the imperfections of their analog counterparts in real-time. As a PhD