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Field
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Processes (CLARA). 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
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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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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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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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-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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, 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
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. Desirable criteria Experience with training or fine-tuning LLMs or other generative AI models Excellent programming skills and familiarity with modern AI frameworks Downloading a copy of our Job Description
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patient–AI interaction design, focusing on how systems such as LLM-based tools, decision support systems, and adaptive health technologies are integrated into clinical workflows and/or patient’s lives
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statistical modeling, including development and validation of predictive models using large-scale data. 3. Proficiency in large language model (LLM) and natural language processing methods for analysis