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research conducted with human subjects, live vertebrate animals, and involving biohazardous agents, which encompass the work of faculty, staff, and students at DePaul and a portion of the $40 million in
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high-level expertise to research on AI safety in multi-agent systems. The appointee will work as part of a collaborative research team to investigate open challenges in AI safety, including surveying and
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, and agent-based modeling for care delivery Health equity, patient access, and system resilience Multi-modal data integration using EHR, claims, environmental, and behavioral datasets The successful
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distributed training, experiment tracking, and MLOps automation. Problem-Solving Skills (15%) – Innovate adaptive fine-tuning, multi-task learning, and agentic reasoning strategies to improve generalization and
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-degree experience in computational systems modeling, simulation, and analytics. Experience with agent-based, biophysical modeling, or multi-scale modeling; OR Experience with analyzing multi-omics data
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generation ● Experience with retrieval-augmented generation, agentic or multi-stage workflows, or knowledge-integrated models ● A strong publication record in top-tier AI/NLP venues (ACL, EMNLP
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Educational NLP with Multi-Agent and Multimodal LLMs for Inclusive and Collaborative Learning School of Computer Science PhD Research Project Directly Funded Students Worldwide Dr Zheng Yuan
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-Service (MaaS) ecosystem. The work will integrate deep reinforcement learning, autonomous agent modelling, and multi-objective optimization to enable predictive simulation, real-time resource management
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decisions between UAV–USV agents, using principles from game theory and multi-agent systems, to optimize cooperation and dynamic task allocation. Signal processing and control algorithm implementation
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to quickly quantify the damage to forest plantations after a cyclone or a tropical storm. There is unrealised potential in using multi-modal computer vision methods that synthesis multi-source Earth