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learning, algorithms, and programming. Prior exposure to reinforcement learning or human-robot interaction is highly desirable, though motivated candidates with a strong grounding in AI/ML and willingness
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the automatic detection of scams, the onus is often pushed back to humans to detect. Gamification and awareness campaigns are regularly researched and implemented in workplaces to prevent people from being
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This PhD project is funded by a successful ARC Discovery Project grant: "Improving human reasoning with causal Bayesian networks: a user-centric, multimodal, interactive approach" and the successful
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This scholarship will provide a stipend allowance of $29,000 AUD per annum for up to 3.5 years, plus $4,000 travel allowance. If you are currently in Australia you are strongly encouraged to apply. If successful, you will join Dr. Roberto-Martinez Maldonado, Prof. Dragan Gasevic, and a strong...
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the social, cognitive, and communicative skills needed to autonomously engage in meaningful, long-term human-robot interactions. Project overview: Social robots are designed to be competent partners that help
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We have several PhD opportunities available in areas such as Multimodal Large Language Models (MLLM) for human understanding, MLLM safety, and Generative AI. If you have published in top-tier
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The detection of human activities is crucial for effective monitoring purposes. The challenge lies in accurately and promptly identifying various types of activities from videos and images captured
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Ecological systems are dynamic and complex. Many ecosystems support human food production and in turn are impacted by human food production activity. This creates feedback loops between ecosystems
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requires substantial human expertise. Conversely, in real-world scenarios and after just a few data samples, humans are able to quickly uncover the underlying pattern of apparently patternless data and to
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information in the spatial context of the task at hand. To achieve this the computer guidance system needs to be aware of the environment through a rich digital-twin model that is kept up-to-date in the face