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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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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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outcomes. Our research seeks to bridge this knowledge gap by using Agent-Based Modelling (ABM) to simulate and evaluate the impact of various green infrastructure design scenarios in peri-urban areas
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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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May 2025 Apply now In human society, communication is an effective mechanism for coordinating the behaviors of humans. In the field of deep multi-agent reinforcement learning (MARL), agents can also
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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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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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that would give you an advantage) Experience in computational modelling (e.g., agent-based Bayesian models, cognitive learning models, machine learning, robotics). Experience in annotation software such as
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. Validation of new types of markets (both those designed above and others) through principled multi-agent simulations, complex systems analysis or other data-driven simulation methods. Fundamental AI techniques
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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