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developing cutting-edge computer vision and deep learning aimed at optimising inspection and monitoring of infrastructure. Applying these advanced technologies to real-world infrastructure challenges through
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developing cutting-edge computer vision and deep learning aimed at optimising inspection and monitoring of infrastructure. Applying these advanced technologies to real-world infrastructure challenges through
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collaboration with good oral and written communication skills. Previous research experience in machine learning, deep learning and/or computer vision is essential.
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Vision 2028 strategy underscores our commitment to reshaping education for the benefit of all. We empower students from all backgrounds with the skills and opportunities to excel in today’s dynamic world
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by Executive Dean Professor Chris Harty, CTE brings together four schools: Architecture & Planning, Construction, Property & Surveying, Engineering & Design, and Computer Science & Digital Technologies
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conducts cutting edge research into discovering new materials for onboard ammonia cracking applications using computational and data approaches. Vision We are seeking PhD student that is motivated by zero
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Engineering, Computer Science or related disciplines. Experience in autonomous system, manufacturing/robotics and machine vision development will be an advantage. To apply please contact the supervisor, Dr Kun
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conducts cutting edge research into discovering new materials for onboard ammonia cracking applications using computational and data approaches. Vision We are seeking PhD student that is motivated by zero
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the foundation of computer vision, monitoring, and control solutions. However, real applications of AI have typically been demonstrated under highly controlled conditions. Battery assembly processes can be
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Are you passionate about cognitive computational neuroscience and eager to contribute to cutting-edge research in perception? We invite applications for a fully funded PhD studentship supported by