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Industry-based HDR project open for Domestic Students in Australia (Citizens and Permanent Residents) at RMIT University in collaboration with Consunet Pty Ltd. The scholarship is supported by
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, including members specialising in biology, microfluidics, machine learning and clinical research from RMIT University and Leading Technology Group (LTG). LTG is an Australian group of medical research
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via RMIT University application portal. Apply via RMIT University application portal. Potential candidates must have a good hold of distributed software systems, machine learning and cybersecurity
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-preserving trustworthy distributed machine learning. In this research, the successful candidates will focus on mathematical backgrounds involved in differential privacy to devise novel scalable approaches
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fairness, privacy and legal guarantees for ADM systems, such as recommender and machine learning based systems. It takes a multi-disciplinary approach and although focused on the transportation focus area
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The successful applicant will conduct research to design and develop novel machine/deep learning based trust technologies for securing IoT services/devices. The successful applicant will conduct
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that combine fairness, privacy and legal guarantees for ADM systems, such as recommender and machine learning based systems. It takes a multi-disciplinary approach and although focused on the mobilities and
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degree with strong skills in programming and machine learning. Please contact Zhuang Li for more information. The project focuses on developing multilingual datasets and advanced methods to detect and
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This scholarship aims to develop practical methods for optimisaton in large supply chain operations. Ideally candidates should have strong AI, machine learning, and optimisation backgrounds
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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