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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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agents (OHRP, FDA, DOD, etc.) as needed for guidance to ensure UMCIRBs satisfaction of regulatory requirements. Draft and maintain Individual Investigator Agreements with individual research team members
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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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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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learning Foundation models, including large language models Agentic AI Multi-agent AI systems Transfer learning Self-supervised learning Federated learning The Postdoctoral Researcher will be primarily based
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”. Learning-based predictive decision-making for autonomous systems under uncertainty: This PhD project is focusing on advancing proactive decision-making in multi-agent autonomous systems by leveraging and
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agents may present a potential hazard. Syringes, needles, and medications are potentially dangerous and must be used with care. Work involving animals in various disease states may expose the individual
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animals with various disease states may expose the individual to viral, bacterial, and fungal agents known to be transmissible to man. Exposure to chemicals and anesthetic waste gases may be potentially
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, or Full Professor whose research and teaching advance core areas of AI, including, but not limited to, generative AI, neuro-symbolic AI, neuromorphic AI, embodied AI, multi-agent AI, human-centered AI
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work on synthesizing multi-source, multi-modal data into a coherent data infrastructure and define the appropriate policies and standards for hosting, managing, and sharing the data typically used