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to understand these dynamics. This project proposes a novel pipeline of ideas to generate tools and techniques to simulate HIV infection dynamics using a multiscale agent-based modelling technique (cells, viruses
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: Coordination Layer: Formulate passivity-based conditions that guarantee agents—modelled as general nonlinear systems—synchronize their outputs or follow desired collective patterns purely through local
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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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for data analysis and modeling. Familiarity with analyzing large-scale healthcare datasets and real-world data. Experience in developing and applying simulation models, including system dynamics, agent-based
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to efficiently navigate high-dimensional decision spaces, leveraging open-source agent-based simulation tools to evaluate accessibility and environmental impacts of urban planning policies. You should have an MSc
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employment. Please indicate the request in your application. Tasks: scientific research and development activities in the field of agent-based traffic modeling and simulation, e.g. on scenarios of sustainable
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direction could be to use the technique of Inverse Reinforcement Learning (IRL) [2], [3]. IRL is an AI-based technique that supports imitation of the preferred system behaviour by using its behavioural
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experience in the following fields. Cyber-physical modelling and simulation Digital Twins Autonomous Agents and Multi-Agent Systems Machine Learning and MLOps Probability & Statistics incl. Python/R Place of
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to simulate sewer networks as dynamic systems, targeting ≥90% modelling accuracy. Train an explainable decision-making agent to optimize interventions (e.g., pipe upgrades), balancing cost, equity, and
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, especially if they have a background in computational and market simulation methods, such as agent-based computational economics. All candidates should have a clear interest in fundamental research, should be