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modelling, and the economics of mental health Support economic analysis of healthcare utilisation, outcomes and costs using national datasets Develop and apply algorithms for cost-effectiveness analysis
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optimisation.” The successful candidate will be involved in developing new mathematical theory and designing and implementing optimisation algorithms relevant to quantum information. The Research Fellow will
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, and may utilise iterative algorithms, machine learning and high-performance computing. Through the Monash Centre for Electron Microscopy, opportunities exist to acquire large experimental datasets using
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the different crystals might have different orientations. As metals are typically used for load-bearing applications, it is imperative to understand the mechanical performance of such materials. Initially, metals
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formula is true or false (EXPTIME vs NP). Can we develop and implement efficient algorithms for this problem? This problem has been attacked using multiple different methods for the past 40 years, without
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account for more sophisticated linguistic notions such as “always”, “possibly”, “believed” or “knows”. Philosophers therefore invented many different non-classical logics which extend CPL with further
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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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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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imaging, based on absorption, provides good image contrast between high- and low-density materials, such as bones and soft tissue. However, it cannot distinguish subtle density differences between soft
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the different actors' beliefs and intentions. We will study the properties of such explanations, present algorithms for automatically computing them as well as extensions to existing frameworks and evaluate