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into the co-design of ultra-low-power AI hardware architectures tailored for edge computing applications. The research aims to develop neuromorphic processors, FPGA/ASIC-based AI accelerators, and intelligent
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, especially precision/high sensitivity circuits (e.g. low current design). Experience writing software to run embedded systems – ideally FPGA code, but microcontroller also very welcome. Good communication
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, or FPGAs control platforms. To be successful at shortlisting stage, please ensure you clearly evidence in your application how you meet the essential and, where applicable, desirable criteria listed in
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, or FPGAs control platforms. To be successful at shortlisting stage, please ensure you clearly evidence in your application how you meet the essential and, where applicable, desirable criteria listed in
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virtual reality systems, code language models, high-level synthesis, Bayesian neural networks, and FPGA-based acceleration. To apply as a Research Associate you must have a PhD (or equivalent) in
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should also be able program, at a basic level, hardware which utilises FPGAs and small embedded processors; these devices are increasingly being used for teaching/research within Electronic Engineering
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of using FPGA tools and provide them the necessary training to use the ASIC tools. The team at Cambridge consists of three investigators: Prof. Robert Mullins (PI), Prof. Timothy Jones and Dr Rika Antonova
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individual with the ability to support dynamic research activities and ensure smooth technical operations. You should apply if Specialist in server, storage, network, and FPGA setup/support. Expert in IT
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interested in PQC, FPGA/processor design, and aerospace cybersecurity. The candidate will join vibrant doctoral community, benefiting from world-class research facilities in the modern Dalton Building. Project
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- Neuromorphic and AI-Optimized Processors – Design AI-specific chip architectures, including neuromorphic and domain-specific accelerators (TPUs, NPUs, FPGAs), for low-power and real-time AI processing. 2- AI