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, hydrogen consumers and financiers; Conceptualise and develop an agent-based model that simulates these stakeholders and their investments in green power and green hydrogen; Analyse and test the effectiveness
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simulated agents. By systematically manipulating the social conditions (cooperation vs. competition, solo vs. group foraging) and landscapes (poor vs. rich resource availability, clustered vs. uniform
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of humans and simulated agents. By systematically manipulating the social conditions (cooperation vs. competition, solo vs. group foraging) and landscapes (poor vs. rich resource availability, clustered vs
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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
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. These data will be complemented by data from a bespoke survey, designed and analysed by other members of the team. The results from the digital ethnographies will feed into spatial micro-simulation and agent
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for data analysis and modeling. Familiarity with analyzing large-scale healthcare datasets and real-world data. Experience in developing and applying simulation models, including system dynamics, agent-based
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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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interviews. Gather and process macro socio-economic indicators from official statistical sources (CBS, INSEE). Support the development of an agent-based simulation model to evaluate the interactions between
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PhD Position: Activating Heritage as a Mediator for Dialogue and Belonging in an Era of Polarization
sustainability in society and active agents shaping narratives By collaborating with heritage sites and the resources of cultural institutions, leveraging their collections, material culture, and local stories as