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scenarios. Your research will map multilevel governance structures and you will co‑create mitigation strategies through participatory workshops. You will model farmers’ adaptation behaviour using agent‑based
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from this PhD project into an agent-based model. This model will be developed by other PhDs in the project team and simulates household adaptation behaviour over time in global flood-prone regions
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and responsible artificial intelligence, combining areas such as reinforcement learning, social and cognitive computational modelling, knowledge representation and reasoning, agent-based modelling. More
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modelling (e.g., agent-based Bayesian models, cognitive learning models, machine learning). Experience in annotation software such as ELAN and PRAAT. Existing peer-reviewed journal publications and conference
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operation including maintenance. Our research builds on a variety of methods, ranging from analytical methods to fast-time traffic, or agent-based, simulations, and from the newest operations research methods
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nature and communities, creating products that do not deplete but enhance the earth and social systems. You will thus work in co-creation with entrepreneurs to develop artistic and art-based approaches
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for image classification and other domains against existing open source LLM (e.g., Llama 3, Phi-3), as well as develop new kinds of attacks, for example based on evolutionary algorithms. 2. Investigate
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governance, simulation and modelling (agent-based modelling, discrete-event simulation, network models), data modelling / interoperability (e.g., ontologies/semantics, data standards, API-based exchange
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-waiting – were successful spies in seventeenth-century England. This is what Nadine Akkerman describes in her book Invisible Agents, the first analysis of the role of female spies in the seventeenth century
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/ Robust) Combinatorial Optimization, Game Theory, and Network Theory, as well as Artificial Intelligence. Potentially, scenarios could be simulated using agent-based, discrete-event, or other techniques