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Field
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of LLMs to accelerators, specifically, use of agentic AI to support intelligent system analysis, aid operator decision-making, automate complex workflows, and enable more adaptive approaches to machine
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Call for Postdoctoral Researchers in Artificial Intelligence (AI) – Focus on Large Language Models (LLMs) for Predictive Maintenance: Introduction UM6P Mohammed VI Polytechnic University is an
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Project and Research Environment Large Language Models (LLMs) are increasingly used in legal question-answer contexts. It is now well known that answers may contain noise, for example, in the form of so
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models, multimodal models, or biomedical/clinical language models Experience with reasoning models, agents, tool use, or compound LLM systems Experience with LLM post-training methods such as RLHF, RLAIF
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into broader health informatics systems. Provides expert annotations for training large language models (LLMs) and NLP algorithms, focusing on healthcare-specific use cases. Presents findings in department
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at the Computer Vision Center (CVC), in Barcelona, Spain. The position is initially for 1 year and linked to the project “Multimodal LLMs for Document Undestanding” (MuDocU), financed by the Spanish Ministry of
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-cell or spatial transcriptomic analysis is desirable. Experience with machine learning, LLMs, AI agents, multimodal data integration, or automated biological interpretation workflows is desirable but not
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into broader health informatics systems. Provides expert annotations for training large language models (LLMs) and NLP algorithms, focusing on healthcare-specific use cases. Presents findings in department
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, distillation from LLMs, acceleration such as KV caching, data synthesis, utilization of external knowledge, multimodal integration, and architecture improvement. We aim for advanced research outcomes
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depth in some of the following areas (not all are required): Large-scale data analysis and learning analytics methods Experimental or quasi-experimental design; validity and measurement Working with LLMs