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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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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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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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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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Program at the Stanford Cancer Institute. She has an academic interest in Precision Medicine and her lab applies cutting-edge sequencing and imaging technologies to better understand skin cancer and rare
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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
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. The project provides a unique opportunity to use clinically relevant animal models, transgenic mice, in vitro and ex vivo cultures, live cell and tissue imaging, single cell technologies, and bioinformatic
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the Department and wider Stanford community to establish new techniques and research directions. • Apply and obtain competitive funding. • Employ advanced imaging, spatial analysis, and sequencing-based