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-negative pathogens (Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa). The project will combine single-cell/single-bacterium imaging approaches with the lab's tissue-engineered
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Experience with machine learning and/or statistical modeling applied to biological data Proven expertise in single-cell data analysis (scRNA-seq and/or scATAC-seq) Interest or experience in multi-modal data
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optical technologies to study mechanisms of cell surface signaling, cancer neuroscience, and protein engineering, integrating molecular biology, cell biology, and systems neuroscience approaches. To support
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of SATURNA, namely Language Models for RNA sequences, Graph representation learning and generative models, Knowledge-Augmented RNA modeling, Computational RNA biology and Experimental stem cell biology and RNA
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which cells sense, adapt, and respond to their environment. We study free-living unicellular organisms as model systems. Using microscopy, quantitative measurements, and molecular perturbations, we seek
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the field of sustainable construction. The research integrates dynamic material value-chain analyses, ownership models, technical performance assessment, and design-for-disassembly strategies to support the