408 phd-position-for-fully-funded-reserch-in-computer-vision PhD positions in Australia
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In addition to the Industry PhD Program Scholarship of $34,000 pa (GST exempt, indexed annually at 3%), there is an industry top-up component valued at $12,000 pa (not indexed). As such
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. This Scholarship will be available for 3.5 years. Applications are now open. Applications are now open. Position will remain open until filled. Position will remain open until filled. 2 available. 2 available
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be closed when the right PhD candidates are selected Application will be closed when the right PhD candidates are selected One (1) One (1) To be eligible for this scholarship you must: Have a Master by
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computer vision and machine learning methods to interpret the photovoltaic (PV) solar farm's condition and perform various inspections and anomaly detection. The research will draw from state-of-art
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Fully online degrees Our collection of courses are taught entirely online, giving you the flexibility to study anywhere, anytime. Our online undergraduate degrees Our online postgraduate degrees Online
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Are you passionate about energy efficiency and developing technology to reduce climate emissions? We are offering a fully funded PhD project with a tax-free stipend of $35,888 per annum for 3 years
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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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Application dates Applications close31 May 2025 What you'll receive You'll receive a stipend scholarship of $33,637 per annum for a maximum duration of 3.5 years while undertaking a QUT PhD or 1.75
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This PhD scholarship is for candidates interested in developing culturally inclusive AI by creating methods and datasets to align large language models with global social and legal norms. This PhD
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This PhD Scholarship is funded by 2022 ARC Discovery Project “Modelling temporal evolution in spatial ecology with dynamical point processes". The world is undergoing rapid environmental change