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Employer
- Delft University of Technology (TU Delft)
- Delft University of Technology (TU Delft); today published
- University of Groningen
- CWI
- Centrum Wiskunde en Informatica (CWI); today published
- Delft University of Technology
- Delft University of Technology (TU Delft); yesterday published
- Eindhoven University of Technology (TU/e)
- Eindhoven University of Technology (TU/e); Eindhoven
- Wageningen University and Research Center
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Field
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an interest (or prior experience) in computational intelligence, AI and/or agent-based modeling techniques. He or she will work closely with researchers in the Electrical Engineering department at TU Eindhoven
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sciences, economics and regulation. Job description The project of the PhD student based at CWI in Amsterdam will focus on techno-economic models (and in particular multi-agent modeling) of energy exchange
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operational constraints and economic motivations across the value chain. To address these challenges, the project will develop multi-modal artificial intelligence methods to characterize metal scrap composition
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multi-agent coordination domains, from mobiltiy, to logistics and multi-robot systems. In this work, we will consider two use cases: (1) a mobility network considering both fixed-line buses and on-demand
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researched by another PhD candidate in the project. The developed methods could be applicable across many multi-agent coordination domains, from mobiltiy, to logistics and multi-robot systems. In this work, we
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for inclusive design and co-creation for children with ASD and ARFID using AI-empowered agents and games. This includes examining how these technological solutions systems can be adapted to support child-led
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) the development of a holistic multi-hazard risk framework capturing cascading effects across systems and scales; (2) the creation of digital environments utilizing real-time data for dynamic risk evaluation; (3
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for inclusive design and co-creation for children with ASD and ARFID using AI-empowered agents and games. This includes examining how these technological solutions systems can be adapted to support child-led
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that the developed methods are robust, adaptable, and grounded in real-world practice. You will apply advanced techniques such as agent-based modelling, quantitative resilience assessment, and risk analysis to
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design principles with stakeholder engagement approaches, ensuring that the developed methods are robust, adaptable, and grounded in real-world practice. You will apply advanced techniques such as agent