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this ecosystem service. The student will map pedestrian networks using GIS and combine this with existing vegetation data. Field surveys will be conducted to validate the spatial data by measuring shade and
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to understand behaviour through the lens of digital footprint/“smart data” datasets, cutting across sectors ranging through health, retail, mobility, energy and communications. Using GI infections as a case study
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infectious diseases such as gastrointestinal (GI) infections, respiratory infections and sore throats. Using GI infections as a case study, the project will compare trends in OTC medication sales to other
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that are conducive to successful completion of the problem at hand. Particular focus will be on multi-robot and multi-agent problems (e.g., navigation, cooperative transport, team-based agent games). The ideal
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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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science”, led by Dr Susan Hegarty. The PhD position will be focused on developing the citizen science hydromorphology framework, and is open to candidates with strong GIS skills and an academic background
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behaviour. In addition, you can use cost-benefit models to explore how an AMOC tipping point may influence financially optimal strategies, and/or agent-based models to explore how an AMOC tipping point will
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develop targeted antiviral therapies against specific viruses; on the other, we work on broad-spectrum pan-virus family antiviral agents. These broadly active compounds are essential for a rapid and
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Multiple PhD Scholarships available - Cutting-edge research at the frontiers of Whole Cell Modelling
Bacterial Adaptation Using Whole-Cell Models: Bacterial populations evolve in response to selective pressures such as bacteriophages, antimicrobial agents, interspecies interactions, and host immune responses
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the MATSim agent-based transport simulation framework. The main task is to enable simulated agents to choose transportation modes, such as car, bus, bike, or walking, based on real-time feedback from