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model of human working memory. During the project, we will follow an intertwined model-experimental approach. First, we will use electroencephalography (EEG) experiments to investigate the neural basis
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aims at developing tools using large language models (LLMs) for the correction of misinformation about climate change in social media. The successful candidate will develop innovative tools leveraging
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material models based on advanced ML methods, and to seamlessly integrate these models into Finite Element Modelling (FEM) to replace expensive and time-consuming experimental procedures, thereby enhancing
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material models based on advanced ML methods, and to seamlessly integrate these models into Finite Element Modelling (FEM) to replace expensive and time-consuming experimental procedures, thereby enhancing
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€ 2,770 (salary scale PhD candidates) gross per month in the first year, up to a maximum of € 3,539 gross per month in the fourth and final year, based on a full-time position. A holiday allowance of 8
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scale PhD candidates) gross per month in the first year, up to a maximum of € 3,539 gross per month in the fourth and final year, based on a full-time position. A holiday allowance of 8% gross annual
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€ 2,770 (salary scale PhD candidates) gross per month in the first year, up to a maximum of € 3,539 gross per month in the fourth and final year, based on a full-time position. A holiday allowance of 8
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will use computational models to explore the minimal functional requirements for self-replication to emerge from polymerising molecules. Instead of simulating specific chemistries in full detail, we will
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: Optimize network design: Develop a robust, scalable thermodynamic–hydraulic framework to size and configure prosumer-based heating and cooling networks under conditions of price volatility, CO2 taxation
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of responsible human-AI collaboration. The successful candidate will become a member of the Multi-Agent Systems Group, Artificial Intelligence Department and will work under the supervision of Dr. Jakob Schoeffer