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, computer vision, federated learning, foundation models, adaptation techniques, multimodal learning, longitudinal image analysis or related areas, evidenced through coursework, research projects
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This project aims to develop a computer vision system capable of detecting and classifying domestic geographic landmarks in images and video content. By categorizing locations such as “childcare
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Are you interested in applying your AI/DL knowledge to the medical domain? This project focuses on the use of AI in Medical Imaging (e.g. CT, MRI, X-Ray, Ultrasound, etc). The work includes
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While deep learning has shown remarkable performance in medical imaging benchmarks, translating these results to real-world clinical deployment remains challenging. Models trained on data from one
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The project involves building and curating a comprehensive food image dataset suitable for mobile AI applications. High-accuracy deep learning models will be trained on this dataset and then
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Research Fellow in Geodynamic Modeling & Surface Processes Job No.: 693562 Location: Clayton campus Employment Type: Full-time Duration: 2-year fixed-term appointment Remuneration: $86,195
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Machine learning has recently made significant progress for medical imaging applications including image segmentation, enhancement, and reconstruction. Funded as an Australian Research Council
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PhD Scholarship Opportunity - Processing intelligence for green metals using in situ X-ray characterisation and machine learning Job No.: 693787 Location: Clayton campus Employment Type: Full-time
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This research focuses on developing and evaluating methodologies for the optimal design of control charts within the framework of Statistical Process Control (SPC). The study aims to determine the
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also explore the role of AI to guide or suggest analytics. Patient Data Analysis, Procedure Planning & Organ Segmentation: we will explore immersive XR interaction techniques for patient data