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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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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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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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, and direct patient care. This is a multi-faceted position that requires a deep understanding of infusion workflows, SOPs, general nursing practice, guidelines, and policies. Key Responsibilities: Review
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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
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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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anemia, cancer and palliative care. Patient care needs are identified through interdisciplinary assessments, team care planning, and a patient classification system. A multi-disciplinary approach is used
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progressed capabilities towards exploiting zero-day vulnerabilities. Frontier models show promising performance when combined with a focused knowledge base and multi-agent architectures. However, in most cases