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, multimodal data, and explainability? This PhD project offers you the chance to develop novel AI methods that make powerful models more transparent, robust, and usable in critical domains such as healthcare and
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conversational AI, paying attention to trust, cultural sensitivity, and affective interaction; Design methods and metrics to evaluate bias, fairness, inclusivity, safety, and emotional responsiveness; Explore
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related discipline in which chemistry and biology have been combined. independent in performing synthetic organic chemistry. experience with (immune) cells, microscopy imaging methods, and/or cell-based
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interaction; Design methods and metrics to evaluate bias, fairness, inclusivity, safety, and emotional responsiveness; Explore applications such as conversational agents, mental well-being, and education, where
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passionate atmosphere. The themes of Health and Well-being, Social-Cognitive-Affective Decision Making, Development and Learning, and Advanced Behavioral Research Methods guide research and education. The
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control over generative shape optimisation. 2 – Explainable AI with LLMs for Transparent Decision-Making in Design Engineering This project combines classic XAI methods with LLM capabilities to generate
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networks, or network science, and relevant background knowledge n methods in machine learning and AI. The successful candidate will focus on innovating the field of network analysis with AI methods. Examples