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Field
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(LLMs), are interacting with human emotions more readily than earlier AI systems, but we still lack frameworks to understand and shape these interactions. These systems often reproduce and even enlarge
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strategies. Your job Climate change is driven in part by complex feedback mechanisms within both natural and human systems. Some of these feedbacks can lead to so-called tipping points: critical thresholds
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crucial; Design interventions to reduce bias and improve fairness and safety in human-AI interaction. The research will combine computational modeling (e.g., NLP, machine learning, deep learning) with human
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governments face in adopting interactive and responsive approaches to these emerging initiatives. As a result, the potential to truly co-create public value is frequently unrealized. A key principle is that
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emotion safety is crucial; Design interventions to reduce bias and improve fairness and safety in human-AI interaction. The research will combine computational modeling (e.g., NLP, machine learning, deep
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the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Are you fascinated by
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- 1 fte Introduction This PhD position aims to investigate how complex temporalities of migration and mobility in urban contexts interact with policies aimed at migration and migration-related
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aims to reduce technical barriers to reproducibility and promote the reuse of computational methods. The interaction with GenAI is not straight-forward and the quality of the output is highly dependent
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human perception and cognition. Experience in: experimental methods, computer rendering or VR/XR, programming. Affinity with multidisciplinary work, combining science, art, and technology. Enthusiasm
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adapt to environmental change, including ecological and evolutionary effects on species interactions, behaviour and community composition. We make innovative contributions to the fundamental research