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Field
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the Large Language Models (LLMs). The successful candidate will work on pioneering research projects that push the boundaries of what AI can achieve, particularly in the domain of multimodal learning. You
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the German Research Foundation (DFG). The priority area contributes to a better understanding of language technology (in particular, large language models, LLMs) and its applicability in the sciences, with a
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). Excellent communication skills in English are essential. Desirable requirements: The following will be considered strong assets: practical research experience with AI, Large Language Models (LLMs), and
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Max Planck Institute for Demographic Research (MPIDR) | Rostock, Mecklenburg Vorpommern | Germany | 5 days ago
rulings, shifting judges’ roles from writing to supervising. We aim at developing a benchmark to test whether LLMs can produce legal reasoning comparable to trained lawyers. (PIs: Engel, Gummadi) In
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collaboration and the broader HEP community. An emerging research program in agentic AI for HEP analysis, developing LLM-based systems with integrated domain knowledge of ATLAS workflows, statistical inference
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censorship. Core responsibilities include: Develop LLM-driven knowledge graphs that construct probabilistic historical priors from bibliographic records, trial transcripts, censorship lists, and apprenticeship
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Postdoctoral Research Fellow with expertise in large language models (LLMs) and electronic phenotyping to join our dynamic team focused on advancing cancer research through innovative data-driven approaches in
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, and demonstrated academic writing and communication skills. Experience designing or using AI-assisted research workflows (e.g., LLM-supported literature synthesis, structured extraction of claims
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developing cutting-edge active-learning (Bayesian optimisation) methods that integrate chemical knowledge by capitalising on Large Language Models (LLMs) as well as human knowledge. You should have a PhD in
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Post-Doctoral Associate in the Center for Interdisciplinary Data Science and Artificial Intelligence
on clinical use cases of interest, (b) building a tailored health-focused Arabic knowledge interactive language model through the development of benchmark datasets, evaluation frameworks, and specialized LLMs