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optimization of large language models (LLMs) and related architectures for generative tasks, continuous learning, indexing or retrieval, support of retrieval augmented generation over many data points from long
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pathways of atmospheric organic reactions. AI-augmented molecular simulations: developing and applying machine-learning force fields and state-of-the-art enhanced sampling to reveal interfacial and
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Keystone project on Addressing socio-technical limitations of Large Language Models (LLMs), particularly for medical and social computing https://adsolve.github.io/ ). The current role involves augmenting
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staffing, employment, or staff augmentation. For postdoctoral researchers, it is not a substitute for a formal ORNL postdoctoral appointment. For professionals, it is not a vehicle for project-based
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of SATURNA, namely Language Models for RNA sequences, Graph representation learning and generative models, Knowledge-Augmented RNA modeling, Computational RNA biology and Experimental stem cell biology and RNA
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dialogue, where meaning emerges through grounding, clarification and feedback. A possible application domain for this research is augmented and mixed reality environments, which require real-time perception
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of the following would be considered an asset: LLM-based clinical decision support, rare disease diagnosis, or diagnostic reasoning systems. Retrieval-augmented generation, agentic AI workflows, prompt engineering
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for large language models and agentic AI systems. Experience designing and developing multi-agent systems, tool-using AI agents, retrieval-augmented generation systems, or autonomous reasoning and planning
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structure methods, quantum Monte Carlo, tensor networks, or quantum embedding methods, etc. - ML-augmented numerical method development. - High-performance computing (HPC
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surgery and augmented reality–enhanced robotic imaging. Duties & Responsibilities Conduct and support research in tele-robotic surgical systems and augmented reality–guided robotic imaging. Collaborate with