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This PhD opportunity at Cranfield University explores how next-generation AI models can be embedded within resource-constrained electronic systems to enable intelligent, real-time performance
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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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place to work, a unique and historic setting – Durham is a university like no other. As one of the UK’s leading universities, Durham is an incredible place to define your career. The University is located
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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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of biological brains. Spiking neural networks (SNNs) can offer increased processing speed and reduced power consumption, especially when implemented on dedicated hardware (neuromorphic chips or FPGAs). Standard
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-power edge AI, microcontroller architectures, FPGA-based systems and VLSI, low-power and resource-constrained systems and analogue and mixed-signal systems. Publish high-quality outputs, pursue external
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place to work, a unique and historic setting – Durham is a university like no other. As one of the UK’s leading universities, Durham is an incredible place to define your career. The University is located