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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 3 days ago
patient-derived organoids (PDOs), patient-derived xenografts (PDXs), patient samples, and mouse models. Our computational methods integrate multi-omics data (transcriptomics, genomics, proteomics
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of the project Bacteria are constantly predated by viruses, bacteriophages. To resist predation, bacteria employ numerous antiphage defence systems, with the most famous being CRISPR-Cas. In our lab we discover
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includes the prefrontal cortex with a focus on selection between stimuli of different value and its plasticity. The project will be carried out by applying “all optical physiology” methods, i.e. a
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well as statistical inferences on model outputs, for pre specified research hypotheses. Suggesting further appropriate methods and analyses. Writing manuscripts in to disseminate research findings. Present summaries
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high-performance numerical experiments, analyze data, and communicate your findings through journal publications and conference presentations. The ideal candidate holds a Ph.D. in Chemical Engineering
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in human factors/systems engineering and in implementation science. Dr. Ramly’s research program develops and tests innovative methods for the human-centered design and implementation of systems
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emulators of similar datasets (e.g. Gaussian Process methods by the project lead). These results will inform the IPCC AR7, and adaptation and mitigation policymaking by other global stakeholders. You will be
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from the membranes: copolymers, detergents, etc. - Cell culture (Sf9 insect cells, HEK mammalian cells) - Protein production, purification, and characterization - Biophysical methods for characterizing
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on estimated movements using eDCCs. The research will focus on data simulated using the Monte Carlo method and real data from clinical SPECT scanners with a parallel collimator, such as those available at LUMEN
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rotation forestry towards continuous cover forestry methods is debated in Scandinavia as a way forward to increase biodiversity and climate resilience. This postdoc project will be based on empirical field