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provide multiple competitive scholarships funded by a national elite HDR training program: Data61 Next Generation Graduate (https://www.csiro.au/en/work-with-us/funding-programs/programs/next-generation
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Synthetic data generation has drawn growing attention due to the lack of training data in many application domains. It is useful for privacy-concerned applications, e.g. digital health applications based on electronic medical records. It is also attractive for novel applications, e.g. multimodal...
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/C++) computer codes implementing a cryptographic algorithm. Although desired, background in advanced cryptography is not a must. Application of a PET algorithm to solve a real-life problem: This
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analysis, contextual analysis, audio feature extraction, and machine learning models to identify and assess potentially dangerous content. Similarly, computer vision models are implemented to analyse images
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management, distributed computing, and energy-aware computing, preparing them for impactful roles in industry and research. Key Components and Example Scenarios Predictive Resource Allocation and Load
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Automating code generation, SQL query formulation, and data preprocessing pipelines is a crucial step toward intelligent and efficient software development. This project aims to leverage large language models (LLMs) to address these challenges by developing a comprehensive framework that...
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operators for these notions. Over the past fifty years, such non-classical logics have proved vital in computer science and logic-based artificial intelligence: after all, any intelligent agent must be able
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Candidates should hold a previous degree (Bachelor’s and/or Master’s) in Computer Science, Data Science, Robotics, Mechatronics, or Software Engineering, with demonstrated knowledge in machine
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these decisions? Required knowledge This project is open to candidates from diverse academic backgrounds, including computer science, data science, learning sciences, or educational technology. While prior
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for Scalable Data Systems and Intelligent Analytics Unsupervised Music Emotion Tagging (Affective Computing) Authorised by: Marketing, Faculty of IT , Monash University . Maintained by: Marketing, Faculty of IT