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an important function in the initiation of embryogenesis. The Team In this collaborative project, you as Postdoc will work together with a PhD candidate, and a part-time technician, to address different aspects
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generative AI, multimodal representation learning, and modelling face-to-face dialogues for our NWO-funded project “Grounded Gesture Generation in Context: Object- and Interaction-Aware Generative AI Models
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profile: A PhD in AI, preferably at the interface of information retrieval and machine learning; Research background in generative information retrieval, with publications in the leading venues relevant
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We are looking for a postdoctoral researcher with experience in generative AI, multimodal representation learning, and modelling face-to-face dialogues for our NWO-funded project “Grounded Gesture
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Large Language Models are known to hallucinate. Techniques such as In-Context Learning, Retrieval-Augmented Generation, Chain-of-Thought Prompting, and Self-Refinement can help reduce hallucinations, but
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shown by PhD related outputs) expertise applying creative learning methods, e.g. artistic methods familiarity with working in international environments and within networks collaboration, pro-activity
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community). What we ask of you We are looking for enthusiastic and curious candidates who meet the following profile: A PhD in AI, preferably at the interface of information retrieval and machine learning
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Employment 0.8 - 1.0 FTE Gross monthly salary € 4,728 - € 6,433 Required background PhD Organizational unit Faculty of Social Sciences Application deadline 16 November 2025 Apply now Join the Work
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Learning, Retrieval-Augmented Generation, Chain-of-Thought Prompting, and Self-Refinement can help reduce hallucinations, but they do not eliminate them entirely. This poses a challenge in applications where
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strategies in psychiatry. This research combines recent advances in machine learning and cognitive neuroscience to contribute to future clinical tools for diagnosing and monitoring neuropsychiatric disorders