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is seeking a highly motivated PhD candidate to work on a fundamental research project on systems and control theory for learning in neuromorphic circuits. Neuromorphic computing is an analog, brain
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sensing systems. This includes advancing novel concepts, architectures and integrated circuit design, focusing on energy efficient signal conditioning between analog/RF/mmWave front-ends and digital domains
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. Development cycle including circuit design, simulation, modeling, layout, verification and measurements. Develop scripts and algorithms for analog IC design Prepare research papers/reports/technology
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promising topology for driver and TIA in advanced semiconductor technology Where to apply Website https://www.academictransfer.com/en/jobs/364085/phd-in-the-integrated-circuit-g… Requirements Specific
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research in the area of analog/mixed-signal integrated circuit design. The role will focus on the development of analog in-memory computing macros for AI accelerators. Experience in tape-outs and industry
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criteria We welcome motivated candidates with strong experience in the following areas: - RF circuits / analog electronics - Electromagnetism / antenna design - Wireless sensing / bioelectronics - Prior
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or python, or analytical modeling), OR optomechanics, OR high frequency devices. You are eager to learn and expand your knowledge! Basic knowledge of analog and digital circuits. Experience with various
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. – knowledge of computer vision; knowledge of deep learning architectures; – Knowledge of C++, Python, Matlab; – Analog/digital circuits IC design capability; – Testing of electronic devices and systems; FPGA
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knowledge of analog and digital circuits. Experience with various techniques for high frequency characterization, e.g., lockin amplifier, oscilloscope, FPGA, and so on. Mandatory experience in programming
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development activities focused on the application of Artificial Intelligence (AI) and Large Language Models (LLMs) to the design of analog, mixed-signal and RF integrated circuits. The work will involve