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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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]) for healthcare and life sciences. AI Agents and Autonomous Reasoning, including the development of autonomous agents capable of multi-step clinical reasoning and planning, as well as systems that utilize Retrieval
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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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recruitment and retention strategies, enhance training and engagement efforts, and cultivate class agents as key partners in annual giving and alumni engagement. Design and implement multi-channel marketing
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polarizing agents for nuclear spin hyperpolarization in NMR spectroscopy and imaging applications. Project Overview: This research aims to leverage radical dynamics to improve spin polarization transfer
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fixed-term position at the School of Science and Technology. The postdoctoral researcher will be affiliated with the Machine Perception and Interaction Lab at Örebro University, which carries out multi
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foundation models and agentic AI models. Experience in large-scale deep learning systems and/or large foundation model, and the ability to train models using GPU/TPU parallelization. Experience in multi
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of computing and healthcare. Methodologies of interest include: Multi-modal learning Foundation models, including large language models Agentic AI Multi-agent AI systems Transfer learning Self-supervised
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the United States, and around the globe. The GHRC supports and advances multi-disciplinary large animal and insect vector research, education, and training opportunities for faculty at Texas A&M and their partners
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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