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Field
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background in developmental neurobiology, cannabinoid pharmacology, and in vivo calcium imaging (fiber photometry). You should have experience or a strong desire to learn ex vivo electrophysiology
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a novel multi-omics approach that integrates high-throughput imaging and machine learning methods with CRISPR/Cas9 screens and saturation mutagenesis to answer central questions about the
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POSTDOC JOBS: HUMAN COGNITIVE NEUROSCIENCE Requisition # 4543 Position Basics Advertising Ends on:Extended Until Position is Filled Advertising Started on:Tuesday, February 10th, 2026
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of synaptic transmission in mammalian brain and human neurons derived from human tissue. In addition, the postdoc will perform molecular, cellular and/or electro-physiological experiments. The Postdoc will
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supercomputer and world-class data facilities. This role sits at the intersection of AI at scale and HPC, giving you unmatched resources to prototype new ideas, run large ablations, and translate methods
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Summary: As a postdoctoral research fellow, this position will be responsible for developing and executing research plans designed in collaboration with a talented team of faculty, postdocs, and graduate
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SURGERY (06740A) Is this split and/or fully grant funded? Yes Duties and Responsibilities A postdoc position is available in Dr. Gahtan’s lab at the Burn and Shock Trauma Research Institute in the Stritch
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 2 months ago
research expenditures as well as for federally funded social and behavioral sciences research and development. Here at Carolina, our highly skilled postdocs play a vital role in our research enterprise and
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Position Overview School / Campus / College: School of Medicine Organization: Radiology Title: Postdoctoral Scholar, Department of Radiology, Diagnostic Imaging Sciences Center (DISC) Position
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tools (e.g., FSL, FreeSurfer, AFNI, ANTs, fMRIPrep, QSIPrep) into standardized processing streams. Support advanced modeling approaches including network analysis, multivariate methods, machine learning