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assessment of lymphatic flow, 2) Advancing methods for contrast-enhanced MRL, 3) Creating ideal contrast agents for MRL, and 4) generating phantom and animal models for MRL optimization and validation
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their appointment. Knowledge of theoretical and/or observational cosmology, particularly including perturbative methods, will be an asset. Candidates with a strong background in other theoretical or data analysis
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as necessary. Analyze data to assess prevalence of lead exposure sources, associations with key outcomes, and spatial trends. Support or lead mixed-methods analysis combining survey data with
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applications, and participate in grant applications. Keep up to date with recent scientific advances, mentor junior trainees, and coordinate projects. Skills Developed: Immunology: acquire cutting-edge methods
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: bacteriology, fluorescence microscopy, electron microscopy, antibiotic assays, biochemical purifications, biochemical assays such as binding assays and protein gel electrophoresis, as well as analytical methods
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pharmacoepidemiologic methods. Experience with NLP or unsupervised learning methods. Prior publications in relevant fields. Required Application Materials: Cover letter detailing research interests and fit
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Substitution in the Blind; Ocular Structures and Physiology; MR Engineering and Methods Development for the Visual System. MRI experiments will mainly be conducted at research centers at the Stanford campus and
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methods to improve prediction model generalizability, model fairness, and generalizability of fairness across different clinical sites. The researcher will have the opportunity to use machine learning and
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The Stanford Abdominal Diffusion Group is seeking thoughtful, motivated and collaborative postdoctoral fellows to join a growing team developing motion-robust multi-shot DWI methods for liver, pancreatic, and
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implementing novel strategies for an Adult Editing System, establishing robust Cas9/gRNA delivery methods for somatic cells in adult organisms. You will collaborate closely with a dynamic, multi-disciplinary