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deep learning theory, Bayesian statistics, and generative modelling, this work will advance our understanding of both the capabilities and vulnerabilities of modern AI systems. This will have potential
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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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Current reseach is in the areas of: Development of biomimetic structures as ultrasound contrast agents Deep tissue imaging using photoacoustic contrast agents All optical photoacoustic sensors
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interaction and human motion analysis Prior knowledge of machine learning/deep learning applied to motion analysis (e.g., relevant courses and research experience) would be an advantage IELTS score of 6.5
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North Queensland. Research projects are developed in collaboration between the successful applicant and their supervisor, and potential topics include: deep Earth structures, crustal mineralisation
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multitude of scales – from the individual, to communities, societies, regions, nations and international. Monash Arts has a deep, supportive and vibrant research culture, led by internationally recognised
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and hands-on experience with AI and computer vision. Solid programming skills in Python, especially with PyTorch. Practical experience with deep learning projects, including working with attention
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5.2: Deep Eutectic Solvents (DES) are increasingly being studied for their potential role in lithium-ion battery recycling. DES has limitation for industrial application due to its poor performance in
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Multiple PhD Scholarships available - Cutting-edge research at the frontiers of Whole Cell Modelling
to test those predictions. By comparing model forecasts with genomic and phenotypic data from the evolving populations, you will test whether a deep understanding of the cell can inform predictions
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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