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scholar will lead the management of research projects across the full project lifecycle, including study design, human research ethics (IRB) submissions, data collection, analysis, and dissemination
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Qualifications: Conferral of doctoral degree prior to appointment start date. Experience and training in biology, stroke and/or cognition, analysis of omics and clinical data, prior work in stroke or cognitive
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computational analysis of large-scale pharmacogenomic datasets. The lab maintains active collaborations with medicinal chemists, structural biologists, and clinical oncologists at Stanford and elsewhere
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candidate will gain expertise in CRISPR screening, drug sensitivity profiling, target deconvolution, and the computational analysis of large-scale pharmacogenomic datasets. The lab maintains active
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computational biology, cancer biology, and/or molecular biology preferred • Experience in image processing and analysis also preferred • The candidate will report directly to the Principal Investigator and will
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protein biochemistry and/or cryo-electron microscopy, including at least one of the following: single-particle analysis, cryo-ET, or 2DTM. This position is ideal for researchers who want rigorous training
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by the Center for Education Policy Analysis and the Education Data Science program) develop cultural competencies (via events organized by the Race, Inequality, and Language in Education program and
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or latent class analyses, latent transition analysis) and other multilevel modeling approaches that account for nested data (both within individuals and across sites) o Mediation, moderation, multigroup
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factor for the human ER membrane protein complex. Mol Cell, 81, 2693-2704.e12. Pleiner, T.*, Tomaleri, G.P.*, Januszyk, K.*, Inglis, A.J., Hazu, M. and Voorhees, R.M. (2020) Structural basis for membrane
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gain training in 2D/3D spatial multi-omics, single-cell spatial pharmacology, AI-enabled tissue analysis, and translational cancer biology, with access to large, high-quality, in-house spatial datasets