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- Eindhoven University of Technology (TU/e)
- Delft University of Technology (TU Delft)
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- Delft University of Technology (TU Delft); Published today
- Delft University of Technology (TU Delft); today published
- Delft University of Technology (TU Delft); yesterday published
- Eindhoven University of Technology (TU/e); Eindhoven
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Field
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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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related field. Strong academic performance (top 25% of your class). Understanding of analog or digital circuit design. Basic knowledge of defects, faults, and electronic test methods. A passion for
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responsibilities will include: Design and develop analog circuits for implementing ONNs for computing. Modeling, simulate and benchmark different computing tasks such as sensor data processing. Explore ONN
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-like operation in GaN Devices. Silicon devices have both nMOS and pMOS to realize power efficient and seamless analog and digital signal conditioning, but is limited to a narrow operation temperature
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We seek you as a PhD candidate to investigate enabling CMOS-like operation in GaN Devices. Silicon devices have both nMOS and pMOS to realize power efficient and seamless analog and digital signal
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recovery mechanisms will also be evaluated and integrated, addressing the susceptibility of analog and in-memory computing to noise, process variation, and soft errors. The primary objective is to design a
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related discipline. Strong background in analog and mixed-signal integrated circuit design. Experience with Cadence tools for schematic design, layout, and circuit simulation. Interest or prior experience
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-circuit-des… Requirements Specific Requirements A master’s degree in electrical engineering, computer Engineering, or a related field. Strong background in analog and mixed-signal circuit design and
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our research team in the field of mixed-signal IC design, focusing on the implementation of sense to compute paradigm. The ideal candidate will have a strong background in circuit design and experience
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elements with controllable stiffness. The project will involve analytical and computational modelling, as well as designing and conducting lab experiments. Key questions include: How to create materials