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, greenhouse, controlled-environment, and field experiments evaluating seed coating integrity, delivery characteristics of plant defense signaling compounds, and interactions with seed pathogens and early-season
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systems. The postdoctoral associate will design and conduct laboratory, greenhouse, controlled-environment, and field experiments evaluating seed coating integrity, delivery characteristics of plant defense
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the area of precision network neurology, with a focus on understanding how risk factors contribute to brain aging. This research is situated within the framework of predictive, preventive, personalized, and
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or bacterial or parasitic) as well as their metagenomic sequence datasets available within the EUPAHW- JIP2 - SOA23 consortium and/or in public databases with an overall aim of predicting and preventing
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or bacterial or parasitic) as well as their metagenomic sequence datasets available within the EUPAHW- JIP2 - SOA23 consortium and/or in public databases with an overall aim of predicting and preventing
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intelligence as applied to trauma systems and acute care surgery. Fellows will engage in cutting-edge research spanning multiple domains, including risk prediction models for surgical complications, clinical
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strong background in the design and implementation of novel machine learning models and their application in biomedical research. Experience with multi-omics data analysis, statistical/computational
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the direction of the Principal Investigator in building a first-of-its-kind Software as a Medical Device (SaMD) that predicts, detects, and manages SSIs by fusing RGB + thermal wound images
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and integration of multimodal neuroimaging, behavioral and clinical data, and building large-scale deep learning models for multimodal neuroimaging datasets to construct predictive network models in
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 1 month ago
of excellence for outbreak analytics and disease modeling, named Insight Net. This position’s efforts will focus on developing predictive and analytic models of infectious disease and will use dynamic models and