30 phd-in-vlsi-design PhD positions at Delft University of Technology (TU Delft) in Netherlands
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23 Mar 2026 Job Information Organisation/Company Delft University of Technology (TU Delft) Research Field Architecture » Design Architecture » Landscape architecture Environmental science » Global
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architectures for next-generation wireless communication. Design ultra-low-jitter, low-spur PLLs and validate them on real silicon. Job description Why this position is important Future wireless communication
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receiver and ADC architectures for next-generation wireless communication. Design time-domain receivers and ADCs and validate them on real silicon. Job description Why this position is important Future
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-efficient digital AI/ML accelerator for real-time transmitter error correction in high-speed RF systems. Co-design and validate on real silicon. Job description Wireless networks are becoming increasingly
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microscope based on this photoacoustics concept. Working as part of a small team of researchers, you get to design and develop the imaging system, and combine it with the ultrafast photoacoustics system
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is a top international university combining science, engineering and design. It delivers world class results in education, research and innovation to address challenges in the areas of energy, climate
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Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description PhD on microbial transformation in contaminated
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addition, to maximize re-use and longevity these adsorbents should also allow for (iii) frequent and (iv) effective regeneration. This PhD is embedded in the recently funded NWO Perspektief project BlueVantage
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of performance, as they are very cautious by design. This, in turn, makes them less practical for problems where speed is of utmost priority. On the other hand, offline learning, such as Deep Learning, often
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this specific structured data. How can we perform inference tasks to learn hidden patterns, like community structure or hidden hierarchies? How can we incorporate domain knowledge to design interpretable models