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materials systems at the molecular level with machine learning. The PhD Student will work with tumour sections to develop multiple instance learning and weak supervision / spatial transcriptomics models
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Martin Australia invite applications for a project under this program, advancing robotic perception systems through monitoring of their machine learning models. Run-Time Monitoring of Machine Learning
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This PhD research scholarship (Learning Lessons from Drug Resistance to Tackle Herbicide Resistance) is funded by the Australian Research Council to support a full-time PhD student to undertake
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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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to frailty assessment could be beneficial. Manual measurements from CT scans, however, are labor-intensive and subject to observer variability. The advent of deep learning in medical imaging presents a
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interested in connecting spatial and spectral information to understand complex materials systems at the molecular level with machine learning. PhD Student A will work with tumour sections to develop multiple
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The Australian Institute for Machine Learning (AIML) offers new PhD scholarship opportunities in Industrial AI. These full-time scholarships support students undertaking their PhDs in AI and machine
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. Through application of a representative learning design framework this project will explore how representative are the training activities undertaken in different in game phase (set play / offensive
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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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Machine Learning for Image Classification. Eligibility You must: We would like you to have: sound knowledge of machine learning, computer vision and image processing strong programming skills. How to apply