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Field
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and implementing an embedded optimisation algorithm on representative hardware platforms to demonstrate feasibility and real-time performance. The primary application will be autonomous 6-DoF Moon
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platform of analogue hardware accelerators, so-called Ising machines, that efficiently speed up these computationally difficult tasks in a way unlike any current digital computer. These Ising machines are a
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significantly reduce the amount of vibration data to be stored on edge devices or sent to the clouds. Hence, this project's results will have a high impact on reducing the hardware installation and operation
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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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Organisation Job description Project and job description Our project will make use sensing technologies (hyperspectral cameras, NIR and Raman sensors), and an edge-compute AI pipeline to sort used
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section Energy Technology and Computer Science, where you will have around 20 colleagues with a mix of research and industrial experience. We work with research, innovation, technology implementation, and
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Everyone is talking about artificial intelligence. But who is developing the necessary chips? We are, for example! Would you like to help drive the development of a new highly efficient AI hardware
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, you will perform benchmarking on materials candidates emerging from CAPeX and collaborative research. Key tasks include: Map out pros and cons of various strategies to upgrade the existing hardware
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Neural Networks (SSM-SNNs). The project includes the co-design and integration of a RISC-V processor for hybrid neuromorphic computing. The research aims to develop ultra-low-power computing chips
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equipment, and have access to valuable industry data. The student will benefit from opportunities to present at leading international conferences. Additional training in software-defined radio, hardware-in