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Field
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Familiarity with brain imaging analysis acquisition Knowledge of multivariate statistics and/or digital signal processing Proficiency in Python. Parallel computing processing experience is highly appreciated
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development and regeneration. To address these questions, we employ a multidisciplinary approach that integrates cutting-edge high-resolution live-cell imaging, advanced microscopy, cell and molecular biology
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curious to deliver work that matters, your journey starts here! The Department of Electrical and Computer Engineering (ECE) ranks among the best in the country. Our research programs are at the forefront
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 2 months ago
Qualifications, Competencies, and Experience . Knowledge of cartilage and/or synovial biology, cell and tissue imaging, mouse experiments. Special Physical/Mental Requirements Must be able to perform wet-lab
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should lead to a first author publication. Develops expertise in T cell biology, mouse models of GvHD/GvL, IBD, or EAE, CRISPR/Cas9 guide RNA library screening, bioluminescence imaging, intestinal
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imaging. The University of Minnesota provides an excellent environment for stem cell and neurodegeneration research, with the University of Stem Cell Institute and the N. Bud Grossman Center for Memory
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Substantial published experience with PET imaging analysis. Experience with EEG data analysis or digital signal processing. Working knowledge of scientific computing languages, including Matlab, Python
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complexes, including large multi-subunit assemblies and membrane-associated proteins. Collect and process cryo-EM data using the Talos Arctica and downstream pipelines (e.g., cryoSPARC and RELION). Integrate
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of materials and devices during switching, combining methods such as laser pump and X ray probe total scattering, WAXS and SAXS, imaging, and femtosecond X ray diffraction to probe structure and dynamics in real
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, QA/QC, harmonization, storage, and processing workflows across heterogeneous binational datasets for the TMDH framework. Support to develop APIs, dashboards, and decision-support tools (e.g., web-based