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coordination of endpoint hardware, including PCs, Macs, phones, and tablets. The role requires the ability to assess hardware requirements, operate the team’s fulfilment processes, and ensure requests
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performance (10–50 Hz) on hardware with constrained memory, power and compute. The project will investigate training, adapting and deploying compact Physical AI models efficiently. Work may cover vision
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, ICML). Students receive regular guidance, research training, publication support, hardware/compute access and Intel engagement opportunities. Entry requirements: Relevant undergraduate or master’s degree
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to design, assemble and test the hardware and real-time analysis software and engage with the wider astronomical and space sustainability communities. Key responsibilities: To understand and convey material