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that release huge amounts of CO2. SusMet focuses on the exploration of carbon-free sustainable metallurgy, employing hydrogen as reducing agent, direct electroreduction (electrolysis), and plasma synthesis
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Embark on a ground-breaking PhD project harnessing the power of Myopic Mean Field Games (MFG) and Multi-Agent Reinforced Learning (MARL) to delve into the dynamic world of evolving cyber-physical
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. Specific projects seeking applications are: Accelerating the discovery of inorganic solar-cell materials via a closed-loop, fully robotic synthesis–characterisation platform driven by multi-agent machine
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basic understanding of, and a strong interest in, one of the following topics: Logic-based reasoning approaches, for example formal argumentation, or Formal aspects of autonomous agents and multi-agent
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supports forming a strong multi-disciplinary and international professional network between PhD-students, researchers and industry. Read more: https://wasp-sweden.org/graduate-school/ . Your work assignments
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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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-Vietnam collaboration, funded by the Research Council of Norway (RCN). The successful candidate will use public health data from Vietnam to develop hybrid agent-based and system dynamics models
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to develop hybrid agent-based and system dynamics models. These models will then be adapted and applied to other ComDisp case studies in the USA, Ecuador, and Turkey. The PhD candidate will be responsible
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03.06.2021, Wissenschaftliches Personal The Albarqouni lab develops innovative deep Federated Learning (FL) algorithms that can distill and share the knowledge among AI agents in a robust and