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at least one deep-learning framework (PyTorch preferred).•A solid grounding in machine learning. Experience with representation learning, generative models, foundation models or multimodal integration is a
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tend to hallucinate facts. By contrast, other AI technologies, such as knowledge graphs and formal reasoning engines, are able to reason reliably, but are less good at handling ambiguity. This PhD
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empirically grounded insights into the aesthetic, lived, and institutional realities of contemporary world literature and its agents. Combining textual analysis with sociological and ethnographic methods, EMLIT
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empirically grounded insights into the aesthetic, lived, and institutional realities of contemporary world literature and its agents. Combining textual analysis with sociological and ethnographic methods, EMLIT
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grounded insights into the aesthetic, lived, and institutional realities of contemporary world literature and its agents. Combining textual analysis with sociological and ethnographic methods, EMLIT aims
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evaluated on a rolling basis until the positions are filled. Suitable candidates may be selected and interviewed before the deadline. Early applications are therefore strongly encouraged.Expected start date
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results), and a motivation letter describing why you are the perfect candidate for this position. It should include the reason(s) why you are interested in this specific position and project, as
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will specifically investigate AI-driven differentiated instruction for both speaking and writing skills. The aim is to generate scientifically grounded insights into the added value of AI