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thinking, agent-based modeling, and system dynamics, thereby linking advanced AI with methods for analyzing, simulating, and designing complex socio-technical systems. You will design and investigate methods
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agent-based models (ABM) to simulate how people move, make activity choices, and interact with their environment; ultimately helping to design equitable, active, and healthy urban spaces. Besides that
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workflow optimization • Network, graph, and agent-based modeling for care delivery • Health equity, patient access, and system resilience • Multi-modal data integration using EHR, claims, environmental, and
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architecture and design for complex socio-technical systems Graph theory, network science, and knowledge representation Agent-based and simulation modeling AI/ML, foundation models, causal inference, and
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studies using a laboratory pilot plant consisting of a perfectly stirred reactor, - Analysis by gas chromatography coupled with a mass spectrometer - simulations of combustion experiments - writing articles
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pipeline of ideas to generate tools and techniques to simulate HIV infection dynamics using a multiscale agent-based modelling technique (cells, viruses, drugs, antibodies, human lymph system, seconds, days
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qualification (usually PhD). Research area: Systems of interacting particles are ubiquitous in natural and social sciences. Typically, they comprise many agents that, through intra-specific and inter-specific
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-funded Environmental Research Data Repository (EnviStor) using agentic AI. This entry-level role is ideal for students looking to gain experience in data analytics and AI collaboration. As an AI Data
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in subjects directly relevant to the specific specialization. It is a requirement that you have: Experience working with Agent-based Modeling and Simulation Experience working with Agent-based Modeling
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four (4) years of post-degree experience in computational systems modeling, simulation, and analytics. Experience with agent-based, biophysical modeling, or multi-scale modeling; OR Experience with