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models (VLMs) on edge hardware. While VLMs have demonstrated strong capabilities in multimodal reasoning and understanding, their high computational and memory demands pose significant challenges for real
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relevant work experience. You will have: Sound technical knowledge of desktop hardware and both standard and customised (in-house) software - knowledge of the University’s Standard Operating Environment (SOE
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hardware-aware AI design, this project explores scalable approaches to improve perception accuracy, system reliability, and responsiveness in dynamic environments. Researchers and students will investigate
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large datasets and developing experimental techniques, including the use of artificial intelligence. There are also opportunities to be involved in the development and testing of new hardware for the next
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room solutions and enterprise-wide management including AVoIP video and audio systems such as Netgear, NVX and Dante. Proven skills in audiovisual hardware/software, AV control system programming and AV
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-route tasks to maintain uninterrupted service. This research area involves developing fault-tolerant systems that adapt to hardware and software failures. Students will work on predictive maintenance and