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Field
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AI and ML theory, foundation models and generative AI, reinforcement learning and autonomous agents, hardware and systems for AI, edge and federated learning, AI security and privacy, quantum machine
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world-renowned research institute alongside faculty, software engineers, PhD students, and PostDocs on the development of cutting-edge AI-ready/agentic infrastructure for data and model discovery, model
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(1-2) Applicants with expertise in one or more of the following areas are encouraged to apply: * Foundation Models * Agentic AI * Reinforcement Learning * Medical Image Analysis Position 2: Intelligent
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prototype knowledge graph-based retrieval for cross-document entity relationships (fund → manager → counterparty → regulatory status) · Experiment with multi-agent orchestration for parallel due
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AI for science, literature-based discovery, or scientific knowledge extraction. Experience building or modifying AI agents, tool-using models, or code generation systems. Experience with high
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the exoskeleton with an AI-based digital health intervention, specifically an LLM-based conversational agent that will deliver support via a companion mobile app. The app will serve as both the user interface
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. Evidence-based Practice Maintains expertise in the ADNP practice model, competency models, and simulation standards of practice. Educates staff on policies and procedures, supporting practice changes based
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at the interface of microbubble formulation chemistry, acoustics, and biomedical engineering, advancing hemoglobin-based microbubble platforms from in vitro proof-of-concept toward in vivo validation
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. Responsible for the configuration, deployment, and lifecycle management of AI assistant platforms, AI agent development environments, and model deployment platforms, as well as the underlying cloud
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population vulnerability. The postdoctoral researcher will play a central role in connecting behavioural decision-making with environmental exposure assessment through the development of an Agent-Based Model