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Job Description The successful candidate will work with Professor Mark Breese on Intelligent computer vision algorithms under a project on “Development of Cone Prism Camera Technology”. We seek a
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Job Description The successful candidates will contribute to research activities related to use of computer vision, machine learning, and analytics to construction safety. The candidate shall work
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Job Description The successful candidates will contribute to research activities related to developing computer vision systems to improve construction site safety. The candidates shall work under
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undertake research in computer vision, NLP, and machine learning To produce research reports and/or publications as required by the funding body or for dissemination to the wider academic community
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systems. Experience in 3D computer vision is preferred. Proficient in programming with deep learning architectures, such as PyTorch, TensorFlow, etc. Skilled at managing multiple tasks across projects and
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: A PhD in Computer Science or relevant fields; Strong background in machine learning, deep learning and computer vision. Prior experience in 3D vision is preferable. Strong publication records in top
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satisfactory performance. Successful candidates will be involved in a project that is related to generative design. Key Responsibilities: To independently undertake research in computer vision and deep learning
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fields. Strong background in machine learning and computer vision. Experience in 3D vision is preferable. Strong publication records in top-tier machine learning or computer vision conferences/journals
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research projects. The candidate will do research on 3D Human Reconstruction, Neural Representations and Rendering for Humans, and Animatable Humans. The goal is to publish in top-tier computer vision and
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-fully supervised learning Result motivated Prior publications in major computer vision (CVPR/ICCV/ECCV) or machine learning (NeurIPS, ICML/ICLR) conferences is a plus The successful incumbent will be