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Field
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, as a doctoral researcher, will: Explore energy–delay efficient unconventional computing architectures through both simulation and experimental prototyping Perform iterative hardware–algorithm co-design
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: Investigate and design optimal computing and communication architectures for hardware acceleration of large-scale machine learning workloads Perform characterization and modeling of electronic and optical
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on massively parallel hardware architectures Combination of programmable logic, tensor processors and general-purpose CPUs for real-time adaption and scheduling services (e.g., AMD Versal platform
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sensor availability, remains an open research area, particularly when grounded in experimental hardware rather than purely theoretical models. The PhD aims to conduct underpinning research on the system
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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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at the internationally recognised IVHM Centre, the research is supported by collaborations with Boeing, Rolls-Royce, Thales, and UKRI, offering a unique environment for cutting-edge work in fault-tolerant hardware
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traffic data processor capable of performing tasks like flow classification, anomaly identification or intrusion detection at Gbps without the need for external hardware or time-consuming cross-plane
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of calculations on a hardware architecture that matches the inherent nature of quantum chemistry electronic structure calculations and with it the opportunity to capture some of the inherent physics, albeit with
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when collecting video games? How have museums historically dealt with similar complex, composite objects (hardware, software, source code, documentation, media, and living histories)? What testimonies
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-on artificial intelligence. To achieve the vision, research will focus on improving the hardware for both 6G devices and space-based satellites, developing signal processing methods that handle large signal