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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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. On the other hand, typical design cycles in industry still make extensive use of low-fidelity simulations which can provide fast but inaccurate solutions depending on the flow complexity. To close this gap
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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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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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Join TU Delft and work together with NXP to build low-power AI accelerators for self-healing analog/RF calibration, fixing noise/offset. Co-design algorithms & hardware and validate on real silicon
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Job description In the global pursuit of safer and more autonomous mobility, a new frontier in automotive sensing is emerging. This PhD project focuses on developing a novel terahertz (THz) sensing
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specifically naval architecture, generative AI is lagging behind. This is largely due to data scarcity in the maritime domain. Unlike media domains where vast datasets are readily available, ship design data is
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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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Published Monday 15 Sep 2025 Deadline Wednesday 15 Oct 2025 Work area PhD Employment 1 fte - 1 fte Introduction As a junior researcher for Work Package 3, you will be based at Khulna University and
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specifically naval architecture, generative AI is lagging behind. This is largely due to data scarcity in the maritime domain. Unlike media domains where vast datasets are readily available, ship design data is