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and aggression, using optogenetics, in vivo imaging, electrophysiology, and sophisticated machine learning/artificial intelligence analyses of mouse behavior. All projects have translational components
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. Research Themes and Projects: We are an interdisciplinary research team integrating single-cell and spatial genomics, lineage tracing, synaptic proteomics, functional perturbation screening, and machine
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/Python coding, next-generation sequencing data interpretation, large-scale data integration, and machine learning. Science: strengthen the ability to formulate hypotheses, design aims to test the
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, biologics, and cannabis. Apply statistical and machine learning approaches (e.g., sequence analysis, latent class analysis, clustering) to examine medication use trajectories and patient subgroups
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. • Develop computational and theoretical models that bridge neural data and behaviour, leveraging modern machine‑learning toolkits. • Drive multi‑lab collaborations across SCENE; co‑author high‑impact
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, robust, and reproducible data analysis. Conventional statistical approaches will be combined with innovations in interpretable machine learning to address each aim from multiple angles. Analysis code will