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on real-world surveillance and safety applications using data from Plymouth Community Homes Digital Living Lab. Ideal candidate Strong background in deep learning, computer vision, and artificial
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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
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Nottingham BBSRC DTP CASE Project Project Title: Deciphering Oral Movements in Health and Disease using MRI Imaging and Computer Vision Research Cluster: (Bioscience for Human Health) School: School
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3.5-year EPSRC funded UDLA PhD studentship. The studentship will start on 1st October 2025. Project Description The UK Government's pursuit of Net Zero and Energy Security heavily relies on developing
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Nottingham BBSRC DTP CASE Project Project Title: Deciphering Oral Movements in Health and Disease using MRI Imaging and Computer Vision Research Cluster: (Bioscience for Human Health) School: School
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engineering, embedded systems design, and Internet-of-Things / Industry 4.0 technologies. Knowledge of computer science principles and modern AI approaches in computer vision and / or time series analysis is a
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and modern AI approaches in computer vision and / or time series analysis is a plus. The position requires strong teamwork and communication skills, reliability, attention to detail, effective time
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Technology, The University of Nottingham. Applicants are invited to undertake a three-year PhD programme in partnership with industry to address key challenges in on-platform manufacturing engineering. The
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. A keen interest on remote sensing is highly desirable. How to apply Applications should be submitted via the Computer Science PhD programme page. In place of a research proposal, you should upload a
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programme of study: Search for the ‘Course Title’ using the programme code: 8060F Select ‘ PhD Electrical and Electronic Engineering (full time)' as the programme of study You will then need to provide