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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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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
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national network of collaborators with similar research programs. Required Qualifications: Highly motivated postdoctoral researcher with: Experience in relational databases, big data curation and analysis
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. The project will also intersect with analysis of extracellular vesicle and with other therapeutically relevant agents. Findings will be validated in human tissue samples to ensure biological relevance. By
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experimental platform for spatial multi-omic analysis of biological tissues. Our lab builds biological measurement infrastructure—engineering systems that standardize how information is extracted from complex
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data analysis, machine learning and computer vision. The position will be based at Stanford University. The fellowship has two primary goals: to advance our research program on the health impacts
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primates or humans – Theoretical neuroscience, machine learning, or AI • Proficiency in Python, MATLAB, or equivalent data‑analysis frameworks. • A passion for big‑picture questions, open science, and