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Field
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infrastructures and cyber-physical systems (CPS) face increasing risks from cyberattacks that exploit vulnerabilities in digital communication networks, embedded hardware, and software. In response
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partners will be a crucial factor for success. Your tasks in the project will revolve around designing and building a DUV microscope with a strong focus on the optical hardware implementation and
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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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algorithms that can tightly integrate physical hardware, sensors, and computational models. This PhD position is centered on addressing these challenges through innovative computational methods, combining
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This PhD opportunity at Cranfield University invites ambitious candidates to explore the frontier of energy-efficient intelligent systems by embedding AI into low-power, long-life hardware platforms
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-level layer implementations - extend hardware developments to use near-FPGA DDR and HBM memories - create functional demos using networks of interest (Yolo, Resnets, LLMs, ...) - create proof-of-concept
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including radiofrequency hardware and software, pre and post procession pipelines, and MRI data analysis. The position responsibilities include writing grant applications as principle and co-investigator and
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implement the required hardware and/or software components, including sensing modules, control algorithms, autonomy modules, or supporting ground systems. Collect and curate relevant datasets from laboratory
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of current systems. Considering this, memristors are innovative electronic components that enable the creation of hardware neural networks inspired by the brain, potentially reducing the energy consumption
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for archiving, indexing and visualization. Our hardware encompasses CPU and GPU-nodes, and software will be designed for both multithreading and horizontal scaling. The PhD student will become part of