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and 45% worldwide. Predictive models based on Artificial Intelligence (AI) techniques will enable risk stratification to implement personalized medicine for prevention and earlier diagnosis of GDM. One
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. For many real-world planning problems however, it is difficult to obtain the full model of the world that captures its complex dynamics. Fortunately, the unknown parts model can be accurately approximated as
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Markov Decision Processes (MDPs) are frameworks used to model decision-making in situations where outcomes are partly random and partly under the control of a decision maker. While small MDPs
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PhD Scholarship – Modelling the social and political drivers of net zero transitions Job No.: 670767 Location: Clayton campus Employment Type: Full-time Duration: 3.5-year fixed-term appointment
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tools to tackle some of the most complex questions in brain science. As a Level A research-only academic, you will contribute to projects that integrate computational models with experimental neuroimaging
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The Opportunity The Manager – Cyber Threat Intelligence (CTI) & Security Agency Relations designs and builds a sustainable CTI practice ensuring compliance with the Australian Defence Industry Security Program
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Neuro-symbolic AI combines the strengths of neural and symbolic methods to efficiently learn and reason over models of the world. Typically, many of the assurances that can be provided by
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into the learned neural models of the world to create a Neuro-symbolic AI that can provide assurance guarantees. Required knowledge A successful candidate should have: a degree in Computer
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, identifying molecular disease signatures and matching them with the most effective therapeutic interventions are essential. The Hudson‐Monash Paediatric Precision Medicine (HMPPM) Program aims to develop and
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, human society and our agriculture, that are typical of complex systems. Ecosystem and social system modelling therefore, including simulation, can play a key role to understand food production and