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Field
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the capabilities of Agents, build with Large Language Models, in a collaborative a hidden profiles task. The scenario places 3 people in collaboration with an Agent in a group chat with the task
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campus, with faculty based on University campuses, at Research and Extension Centers and in every Arkansas county. It consists of the Arkansas Agricultural Experiment Station (AES) and the Arkansas
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interdisciplinary pipelines to identify effective RNA drugs against human diseases: AI-driven RNA discovery – using AI agents to prioritize the therapeutic potential of human lncRNAs (supported by the NHLBI
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output regulation for uncertain multi-agent systems”. Key Responsibilities: The Research Fellow will work conduct research on the project “Reinforcement learning based event-triggered prescribed-time
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Socially-Aware AI agent to enhance team training by providing real-time insights and actionable feedback from multimodal data. We envision that humans and agents will work in teams, complementing each other
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prompt engineering, embeddings, retrieval-augmented generation (RAG), agent or tool-based workflows, or application-level architectures. Ability to work collaboratively across disciplines and communicate
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part of the COP-PILOT project, a solution will be developed to streamline network management and orchestration tasks, incorporating LLMs as a method for implementing the intent-based management paradigm
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of an agent-based model for Brazil The post-holder must have a postgraduate degree, ideally a doctoral degree, in a relevant topic and will have expertise in analysing large quantitative datasets and in
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using ML, network-based and agent-based models Integration of histological, clinical and transcriptomic data for precision oncology Translational and innovation-oriented projects linked to clinical
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of the following activities: Activity 1: Assessment of the direct effects of the biological control agent Trichilogaster acaciaelongifoliae Assess the establishment of the biological control agent along