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noncrystalline biological and materials systems; NMR-based studies of antibacterial agents, their interactions with bacterial cells, and their mechanisms of action; and Integration of NMR with complementary
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of therapeutic targets and novel anticancer agents for endocrine cancers. Required Qualifications: • PhD in cancer biology, cell biology, molecular biology, bioengineering, or a closely related field
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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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an AI-enabled instructional coaching initiative, which advances a broader agenda of AI for high-stakes social interactions. This work is motivated by a challenge pervasive in early childhood and beyond
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for strategies to understand and treat bacterial infections, with intensely translational efforts focused on discovering and developing new antibacterial agents. We are advancing antibacterial compounds already
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. The project will also intersect with analysis of extracellular vesicle and with other therapeutically relevant agents. Findings will be validated in human tissue samples to ensure biological relevance. By
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, fibrosis-enriched imaging phenotypes, multi-omic causal discovery, and AI-enabled target prioritization. The fellow may also contribute to projects related to scientific discovery agents and AI-assisted