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system dynamics, agent-based modeling, and discrete choice experiments. A passion for improving healthcare systems, particularly in oncology, and an understanding of patient preferences in the context
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team, the PhD student will support the development of discrete choice experiments in two countries, and agent-based modelling, as we plan to model how doctors make job choices among alternative hospitals
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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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analysis of mobility behavior, the application of agent-based models and road space analysis, particularly for road safety. Research on walking and cycling as a cross-cutting issue has a high priority in all
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that integrates climate resilience, equity, and cost-effectiveness into infrastructure management, aligning with UN SDGs 6 (clean-water) and 11 (sustainable-cities). Objectives Develop physics-based ML models
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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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study. The student would be based in the Department of Computer Science in the Faculty of Environment, Science and Economy at the Streatham Campus in Exeter. Computing systems increasingly operate in
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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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of the PhD student based at CWI in Amsterdam will study integrated hydrogen-electricity markets. In particular techniques from Artificial Intelligence and multi-agent systems for modelling new types of markets
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. Examples of topics include algorithmic fairness in network analysis, developing network embedding frameworks for real-world network datasets or AI models based on agentic LLMs for simulating real-world