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group has implemented state-of-the-art deep learning for underwater communications; deep learning models underwater environment based on real data. Our preliminary study shows that state-of-the-art deep
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deep learning. The purpose of this scholarship is to support a PhD student to contribute to the advancement of infrastructure monitoring technologies with strong industry collaboration. Student type
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deep learning, imaging and data analysis would be helpful for this project. Must be eligible to enrol in PhD programs at Curtin University. Application process Please send your CV, academic transcripts
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structural health monitoring, especially on computer vision, image processing, machine learning, deep learning, signal processing and data analysis techniques, are preferred. Application process To apply
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publications and research experiences in structural dynamics and structural health monitoring, especially on computer vision, image processing, machine learning, deep learning, signal processing and data
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Status: Closed Applications open: 1/07/2024 Applications close: 18/08/2024 View printable version [.pdf] About this scholarship Description/Applicant information Project Overview Deep learning has
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-refinement for finite element and scientific deep learning methods (gradient-free adaptation, generalized stochastic gradient descent methods) Salary for PhD students: is AUD32K per annum, tax free