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computation in science and engineering; Advanced materials and manufacturing; Energy and environment; Future cities; and Life sciences We are seeking an individual passionate about undertaking research in
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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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The world is dynamic, in constant flux. However, machine learning typically learns static models from historical data. As the world changes, these models decline in performance, sometimes catastrophically so. This PhD will develop technologies for addressing this serious problem, building upon...
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testing approaches that can be used to verify that machine learning models are not biased. Required knowledge Software engineering, software testing, statistics, machine learning
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Baccalaureate student. Commencing one of the following scholars programs at a Monash campus in Australia: Bachelor of Pharmaceutical Science (Advanced) Honours Scholars Program Bachelor of Pharmacy (Honours
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Monash Education PhD Scholarship - Engineering the Future: Safety Risk Intelligence in Early Childhood Job No.: 686175 Location: Peninsula campus, Melbourne and rural Victoria Employment Type: Full
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🎯 Research Vision The next generation of software engineering tools will move beyond autocomplete and static code generation toward autonomous, agentic systems — AI developers capable of planning
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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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for inference, yet differs from standard Bayesian approaches through its information-theoretic foundation. The MML87 approximation achieves computational tractability while remaining virtually identical to Strict