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@rmit.edu.au Please send your CV to akram.hourani@rmit.edu.au Required Skills: Programming and simulation: strong experience in Python or MATLAB. Mathematical modelling: probability, optimization, or multi-agent
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, optimization, or multi-agent interactions. Machine learning: reinforcement learning, or multi-agent systems. Signal processing: spectrum sensing, localization, or radio environment modelling. Optimization and
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engagement methodologies for the design of large language model (LLM) agents within digital health interventions. Stakeholders in this context include subject matter experts—such as clinicians, healthcare
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, optimization, or multi-agent interactions. Machine learning: reinforcement learning, or multi-agent systems. Signal processing: spectrum sensing, localization, or radio environment modelling. Optimization and
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(https://www.bookbotkids.com/ ) is an AI-powered platform and app designed to enhance children’s reading engagement and fluency through interactive AI agents using advanced language models. About the
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orally and in writing. Experience in at least one of the following topics: mathematical biology, mathematical modelling, agent-based modelling, Bayesian inference, optimisation Demonstrated ability to use
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and high performing team, responsible for providing support and general direction to an administrative team and Contact Centre Agents within a work unit. You will conduct inbound and outbound campaigns
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leadership, role model the RMIT values and behaviours and act as a change agent within a large organisation. Demonstrated conceptual, planning and organisational skills with the proven ability to lead projects
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to the following: Develop a comprehensive understanding of the oxidation kinetics and mechanisms using different oxidising agents. • Develop a comprehensive understanding of the leaching kinetics and
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, integrated assessment or agent-based models) and/or research on sustainability transitions and transformations will be highly regarded. Strong communication skills and the ability to work independently and as