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Post-Doctoral Position in Deep Learning for MRI Reconstruction at Yale University Title: Postdoctoral Associate, Yale School of Medicine Department/Division: Radiology and Biomedical Imaging
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. This role enables postdocs to gain expertise in causal analysis within complex, non-probability observational samples while engaging in exciting applications that harness and integrate data from various
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in vivo mechanotransduction. Investigate RNA-mediated processes governing cellular responses to mechanical cues. Utilize advanced molecular and imaging techniques to study RNA localization and function
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analyse complex data from emerging genomic pathology approaches, including CRISPR, single cell sequencing, spatial transcriptomics, and image analysis to address biologically- and clinically-driven
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and cannabinoids, combining molecular neuroscience, genetics, electroencephalography, imaging, and psychopharmacology. We are deeply committed to training the next generation of scientists and
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applied machine learning/deep learning with applications to either language, signals, or images. Required Skill/Ability 4: Demonstrated strong ability to communicate technical ideas and results to non
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was awarded a NIH K99/R00 Pathway to Independence Award and will be happy to mentor postdocs for their career award application. Our current project can accelerate the development of methods/technologies
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. This role enables postdocs to gain expertise in causal analysis within complex, non-probability observational samples while engaging in exciting applications that harness and integrate data from various
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responses to mechanical cues. Utilize advanced molecular and imaging techniques to study RNA localization and function. Collaborate within a multidisciplinary team at the intersection of RNA biology and
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into the effects of cannabis and cannabinoids, combining molecular neuroscience, genetics, electroencephalography, imaging, and psychopharmacology. We are deeply committed to training the next generation of