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healthcare domains is highly desirable Experience building well-annotated, longitudinal databases integrating clinical data, images, and biospecimens Healthcare database experience (Epic Cosmos, claims
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infections using electronic phenotyping, supervised machine learning, live Epic/FHIR implementations for silent deployment, and multi-site data coordination. https://reporter.nih.gov/search
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will use a combination of scRNAseq, spatial transcriptomics, and highly-multiplexed imaging to understand how human macrophages respond to the early stages of cancer development. They will be a part of
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mechanistic understanding of polar lobe formation at the molecular, cellular and biophysical level. You will adapt live imaging, genetic and molecular manipulation, and biophysics assays to embryos of several
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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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profile of the Laboratory can be found at https://www.nivs-lab.org/ (link is external) . Required Qualifications: Ph.D. in Biomedical Imaging, Neurobiology, Bioengineering, Medical Physics, or related areas
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the United States as well as clinical imaging and testing data from Stanford. Project themes will include developing models using EHR data to predict outcomes in ophthalmology and glaucoma, as well as investigating
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whole-body cancer detection. We are interested in both technical development and clinical translation pipelines, leveraging resources at the Lucas Center for Imaging, synergies across the clinical MRI
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imaging; cellular and molecular biology studies and assays including for example cell culture and transfections, qRT-PCR, RNA and DNA isolation and preparation, ELISAs, tissue histology and microscopy, and
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postdoctoral fellow with interest in organic chemistry and radiopharmaceutical development. Successful candidates will join the Molecular Imaging Program at Stanford within the Department of Radiology, Stanford