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will build on research that detects different types of uncertainty in deep neural networks, and we will connect this uncertainty to interactive data collection, e.g. in the form of a dialogue with the
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. You will develop dynamic models and apply them, for example, to analyze sociotechnological networks and to model interactions between humans and AI agents (such as LLM-based chatbots and autonomous
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We are looking for a PhD student in Visual Learning and Communication with a focus on interactive visualization, visual learning, science communication, and educational science, formally based
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Environmental Change carries out research and education on the interaction between environmental and society in an analytically innovative way. The Division offer PhD, Master and Bachelor studies specialising in
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background in virus-cell interactions, molecular virology/cell-biology We want you to have: An experimental background, including in vitro cell experiments using organoids Meritorious for the position
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will focus on developing theoretical and algorithmic foundations for goal-oriented, semantics-aware communication enabling timely and reliable cloud-to-agent interactions. For more details on semantic
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such as healthcare, finance, cy- bersecurity, and autonomous vehicles, where they interact dynamically with external knowledge sources, retain memory across sessions, and autonomously generate responses and
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(e.g., model compression/simplification and hardware-aware optimization). We are also interested in how resource-efficiency interacts with broader sustainability aspects of machine learning such as
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inference and deployment costs (e.g., model compression/simplification and hardware-aware optimization). We are also interested in how resource-efficiency interacts with broader sustainability aspects