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NMR studies of intact bacterial cells, cell walls, and extracellular matrices, as well as industrially relevant polymers and catalysts; Structural and compositional analysis of functional amyloids
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and AI-based approaches, including predictive modeling, stratification, explainable AI, and integrative multimodal analysis. The scholar will have opportunities to lead first-author publications
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such as transformers, self-supervised learning, multimodal learning, generative models, graph neural networks, or foundation models. Experience with structural and/or functional brain modeling. Familiarity
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brings together a global, multidisciplinary network of collaborators and is grounded in a clear mandate: to generate high-quality evidence and build research capacity to meaningfully improve care for
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national network of collaborators with similar research programs. Required Qualifications: Highly motivated postdoctoral researcher with: Experience in relational databases, big data curation and analysis
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aspirin-responsive molecular networks. Using high-throughput multiomic approaches, the project will define aspirin-induced changes in trophoblast signaling, inflammatory pathways, and vascular regulatory
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gain training in 2D/3D spatial multi-omics, single-cell spatial pharmacology, AI-enabled tissue analysis, and translational cancer biology, with access to large, high-quality, in-house spatial datasets
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for action ("affordances") shape neural representations, perception, and behavior. Why this position? You will sit at the center of a uniquely cross‑disciplinary team and work closely a network of