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-scale clinical data and the use of LLMs across multiple data types and sources is desirable. The successful candidate will contribute to publications, collaborative webtools, presentations, and future
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) to organize, filter, and cross-reference degradation reports across stressors, materials, and module architectures Collaborate with team members developing LLM-based literature extraction and agentic reasoning
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, and Large Language Modelling (LLM). Conduct extensive numerical experiments to validate and evaluate the performance of the proposed models. Present research results as academic papers and reports
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for monitoring and managing animal environments. Highly motivated in design and development of reliable LLM-based agents, integrating APIs and indoor environmental control systems, and translating natural
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drugs, and related ontologies. • Design components of the AI pipeline for enrichment and reasoning over technical life sciences data using large language models (LLMs). • Manage the storage and retrieval
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improve assessment and grading efficiency and effectiveness. AICET is seeking a highly motivated and independent Postdoctoral Research Fellow. Our research focuses on the impact of LLM platforms / tools
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(RL) training for large language model (LLM) agents. Prepare and submit conference papers. Co-supervise undergraduate and/or graduate students. Support teaching activities, including course preparation
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(AI4S) research, to develop AI software powered by large language models (LLMs) for process engineering and materials discovery, to mentor students, and to contribute to grant writing and publications
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and AI-enabled threats using large language models (LLMs), artificial intelligence techniques, and empirical security analysis methods. Support the design and implementation of research prototypes and
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communication technologies is driving the progression of modern AI. However, current efforts are predominantly concentrated on Large Language Models (LLMs) tailored for industrial applications, leaving AI