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Field
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Keystone project on Addressing socio-technical limitations of Large Language Models (LLMs), particularly for medical and social computing https://adsolve.github.io/ ). The current role involves augmenting
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track record in one or more of the following areas, or a combination of these areas: Knowledge-grounded artificial intelligence and knowledge graphs, including large language model (LLM) and retrieval
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Postdoctoral researcher (17 months): Ethics and Epistemology of LLMs4EU: Design, Data and Deployment
regarding language technologies and especially Large Language Models (LLMs), a market currently dominated by U.S. companies. The project builds on existing European initiatives to ensure LLMs, and their
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year. You will be investigating the safety and security implications of large language model (LLM) agents, particularly those capable of interacting with operating systems and external APIs. This project
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particular. By implementing LLM‑driven agents that plan the analysis workflow, call established image-analysis modules and judge their own output, you will streamline image processing efforts and enable
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to industry and developments with Deep Learning (DL), Computer Vision (CV), Transformers, Large Language Models (LLMs), Natural Language Processing (NLP). Mandatory requirements • Bachelor's degree
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Intelligence (DFKI), invites applications for a postdoctoral research position. The group develops foundation models, large language models (LLMs), and agentic AI systems for scientific discovery, engineering
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). This interdisciplinary project investigates how AI — specifically large language model (LLM)-based agents — can act as adaptive social agents to support students' collaborative learning in Challenge-Based Learning (CBL
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, supported by Large Language Models (LLMs). Mandatory requirements: The candidate must hold a Ph.D. in Computer Science or a closely related field. Desirable requirements: Experience in Information Retrieval
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optimization of large language models (LLMs) and related architectures for generative tasks, continuous learning, indexing or retrieval, support of retrieval augmented generation over many data points from long