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PhD Position in Causal Agent-based Modelling of Complex Social Systems Faculty: Faculty of Science Department: Department of Information and Computing Sciences Hours per week: 36 to 40
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working closely with collaborators; familiarity with or a keen interest in developing mechanistic models of dynamical biological systems (differential equation-based modelling, agent-based modelling
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interfaces, and ethics and regulation. What you will be doing Inform a research agenda on the PhD topic for a timespan of four years. Develop mechanisms, interfaces, models, and systems for responsible AI
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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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with established causal models. Ultimately, you will design algorithms for causality-based analysis and counterfactual recovery of liveness violations. Information and application Are you interested in
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computational models and mechanisms that enable AI agents in Hybrid Human-AI teams to learn, adapt, and utilise shared team norms through interactions to ensure their actions are aligned and justifiable
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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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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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models. However, based on our earlier findings we noted that many of the drugs do not penetrate the mycetoma grain. In this project we are therefore looking for an enthusiastic PhD candidate who will test
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querying of AI models to intelligent AI agents’ concepts, through agentic workflows. These are among the prime targets of the newly approved AIEXPERT project: “An agentic, multi-layer, GenAI-powered backbone