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a suit of fast electronics (FPGA) that will allow the following achievements: 1) To rapidly repeat single-particle experimental dynamical trajectories to gain sufficient counting statistics in order
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to reconfigurable / FPGA platforms, formal methods for reliable digital design, and novel device and memory technologies for neuromorphic and edge-AI computing. Our impact spans multiple sectors, including
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of electronics platforms (such as Arduino, microcontrollers, and FPGA) to include programming of these devices. Specialist skills required in some or all the following: electronic system building and testing
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analogue / digital / mixed-signal ICs and intelligent sensing to reconfigurable / FPGA platforms, formal methods for reliable digital design, and novel device and memory technologies for neuromorphic and
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limited to digital electronics (including FPGAs and VHDL) distributed network control, Data Integration, Management and Cybersecurity and integration of hybrid/electric vehicles into energy infrastructure
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significant prior experience of: power semiconductor switching converters such as oscilloscopes programming MicroSemi FPGAs in the Libero environment low level programming of embedded C++ in Infineon Tricore
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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. AI-Driven
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development proposals and funding bids. The successful candidate will have significant prior experience of: power semiconductor switching converters such as oscilloscopes programming MicroSemi FPGAs in
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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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parallel processing, FPGA coding and analysis, along with Machine Learning and AI based image analysis. The final aim of the project will be to generate in-situ / live film profile data to coating line