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This PhD project is part of a larger project that aims to explain the uncertainty of Machine Learning (ML) predictions. To this effect, we must quantify uncertainty, devise algorithms that explain
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School of Electrical Engineering and Computer Science Full-time (100%), fixed-term position for up to 3 years Base salary will be in the range $80,448.78- $107,104.10 + 17% Superannuation (Academic
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the headspace website. Possible approaches to addressing this challenge might include: Developing algorithms to identify patterns and preferences based on service users’ previous content engagement
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This project draws on a recent Dagstuhl Seminar (https://www.dagstuhl.de/en/program/calendar/semhp/?semnr=18322) that brought together leading experts from industry and academia, including those who
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This project focuses on developing algorithms capable of automatically identifying and categorizing mobile ringtones. This involves leveraging machine learning techniques to analyze audio signals
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Computational simulations are now widely employed to study the behaviour of social systems, examples being market behaviours, and social media population behaviours. These methods rely heavily
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systems and swarm robotics. The project builds on well established computational and mathematical modelling techniques to achieve its aims. Departure points will be agent-based simulations, optimisation
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. With the widespread adoption of ML algorithms for data analysis and decision-making, preserving the privacy of individuals' data has become a paramount concern. The project focuses on exploring
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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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Research Training Program (RTP) Stipend Research Training Program (RTP) Scholarships, funded by the Australian Government, support both domestic and international students undertaking Research