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Field
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elements like Physical Unclonable Functions (PUFs) and True Random Number Generators (TRNGs) to secure hardware components. Embedded Trust Protocols: Design protocols that establish and maintain trust within
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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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shift in the world of hardware design. On the one hand, the increasing complexity of deep-learning models demands computers faster and more powerful than ever before. On the other hand, the numerical
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hardware-software prototype for Non-Intrusive Load Monitoring (NILM) that can provide real-time, interpretable energy-saving suggestions to households—completely on-device. This role involves applied machine
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Computing (Hardware for Artificial Intelligence) Reference Number: IV-151/25 Are you excited about designing hardware that mimics biological intelligence with the aim to explore and understand how the brain
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applied research, bridging academia and industry. Students will have access to state-of-the-art laboratories, hardware/software resources, and design facilities, supporting AI-powered electronics research
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to state-of-the-art laboratories, hardware/software resources, and design facilities, supporting AI-powered electronics research. This project will be conducted within Cranfield’s Integrated Vehicle Health
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, Cranfield fosters innovation through applied research, bridging academia and industry. Students will have access to state-of-the-art laboratories, hardware/software resources, and design facilities
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intelligence through hardware design. To this end, both the hardware foundation and the underlying hardware are continuously being developed. The design flow of these circuits and their (sub)systems is of
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(coordination) and safety constraints can be intractable. Your work will bridge this gap by providing generalizable, provable design approach that apply across a wide range of networked systems. This 3.5-year PhD