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privacy-enhancing techniques such as secure multi-party computation, homomorphic encryption, differential privacy, and trusted execution to design algorithms and protocols to secure ML models within
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The brain is a complex machine and brain function remains yet to be fully understood. This project works at the intersection of dynamical modelling, statistical signal processing, statistical
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research and cybersecurity research, notably one current direction is on advancing the latest generative AI models for cybersecurity, or vice versa: using cybersecurity to attack AI. The student is free
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equivalent, with expertise in nuclear and/or maritime engineering Demonstrated research ability that supports the School's research strengths hydroacoustics, modelling and computation, numerical and
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Federated learning (FL) is an emerging machine learning paradium to enable distributed clients (e.g., mobile devices) to jointly train a machine learning model without pooling their raw data into a
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. This project aims to enable the widespread adoption of such tools by: Aims Creating a pre-trained model that can detect rodent body part locations in videos of common behavioural tests, without requiring manual
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This is one of our CSIRO Next Generation AI graduate programme PhD projects with Future Wellness Group: https://www.monash.edu/it/ssc/raise/projects/personal-future-health-prediction Note: *** Must
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models, such as ChatGPT and GPT4, incorporating the cutting-edge techniques in the other areas, such as reinforcement learning, causality and GFlowNets, to devise novel active learning algorithms for NLP
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-disciplinary team of clinician scientists and computer scientists to develop diagnosis/predictive/treatment/robotics surgery models of diseases of interest using multimodal medical data, consisting of images
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Agent-based computational simulations are now widely employed to study the evolution of behaviour, e.g., predator-prey simulations, the evolution of cooperation and altruism, the evolution of niches