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Field
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Provenance Index, and any images of content from which that data was derived Extract text from internal and external provenance documents with LLM-powered OCR/HTR Extract named entities from the text, and
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quality of human reasoning – specifically the capacity for genuine engagement with views that differ from one’s own (what the programme terms “doxastic plasticity”). The programme develops and deploys LLM
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the registered research protocol; conducting case-based, qualitative comparative analysis (QCA), and LLM-assisted qualitative analyses; and leading the development of peer-reviewed manuscripts, public-use datasets
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experimentation in the area of Multi-agent Agentic AI systems applied to 6G network and service management. By leveraging recent advances in LLMs and agentic tools (MCP, LangChain, etc), the project will design
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assessment criteria, which will be benefit are: Knwoledge and experience of cloud, monitoring & automation foundation Experience in foundation models and Large Language Models (LLMs). Experience in teaching
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with user studies, preferably qualitative methods such as interviews, think-alouds or focus groups; significant coding experience in Python; experience with LLMs, in particular as part of agentic systems
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programming capability is necessary. Supplemental Qualifications Preferences will be given to those who have research experience in large language models (LLMs)/foundation models (FMs), single-cell analysis
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fathers) You will: Define AI-ready data standards: Establish and maintain guidance on metadata and formatting requirements for DOE environmental datasets. Build automated checks and tools: Develop LLM
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the integration of AI components transforms the nature of software systems (SE4AI). From an architectural perspective, the research investigates how the inclusion of AI elements—such as LLMs challenges conventional
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University Abu Dhabi invites applications for a Post-Doctoral Associate position, to work in the area of research and development (R&D) of next-generation Edge-AI and Embodied-AI Systems with tiny-LLMs, tiny