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Posting Details Student Title Classification Information Quick Link https://chapman.peopleadmin.com/postings/41047 Job Number SE235524 Position Information Department or Unit Name IRES Position
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 18 hours ago
LLM Engineer Position Number 20078673 Vacancy ID N000892 Full-time/Part-time FTE 1 Hours Per Week 40 Position Location North Carolina, US Hiring Range Proposed Start Date 10/12/2026 Estimated Duration
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schools in the world. For more details, please view https://www.ntu.edu.sg/mae/research . Position Overview We are seeking a highly motivated Research Fellow to join our research team focusing
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into persona representations that condition LLM agents; designing and running evaluations to gauge the validity of synthetic results; developing LLM-guided adaptive experimental designs to enable
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timely research question: How can Large Language Models (LLMs) and intelligent agents support transparent, scalable, and auditable clinical data harmonization? We are particularly interested in: LLM-driven
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Intelligence (LLMs, RAG) and Cloud services. Functions to be developed: Assist in optimizing data ingestion, preparing datasets, and designing vector database structures/bases for semantic queries. Design
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technologies through core facilities and tech watch Direct connection to a growing team of LLM engineers at VIB Part of a dynamic research center with other groups sharing this mission A competitive salary and
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interests in biomedical NLP and medical LLMs, multimodal and foundation models, ophthalmology and medical imaging AI, and real-world applications in biomedicine and healthcare. Please visit https
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high-level information extraction systems by conducting full fine tuning, fine tuning, LoRA tuning w.r.t. material knowledge against LLMs. Research results should be disseminated to international
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, or research artifacts. References [1] G. Sanmartino, M. Urban, P. Papotti, and C. Binnig. The Stretto Execution Engine for LLM-Augmented Data Systems . 2026. https://arxiv.org/abs/2602.04430 [2] D. Satriani, E