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-driven research group working at the intersection of computational genomics, clinical artificial intelligence, and imaging genetics. This position offers an exciting opportunity to develop novel algorithms
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quantitative genetics and maize breeding. -Utilizes skills and knowledge in these and other areas to complete research projects leveraging new data extraction and analysis algorithms and connecting
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/equilibrium reconstruction from limited, noisy diagnostic measurements. Scenario Optimization: Develop plasma scenario optimization workflows leveraging nonlinear programming, genetic algorithms, and
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acoustic propagation that are applicable to a wide range of ocean environments. (40%) Lead efforts to translate propagation and uncertainty models into computationally efficient algorithms that can be
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 6 days ago
to the development and validation of computational methods that integrate images with other multimodal data. The postdoctoral research associate will design, implement, and evaluate algorithms and models
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 10 hours ago
to the development and validation of computational methods that integrate images with other multimodal data. The postdoctoral research associate will design, implement, and evaluate algorithms and models
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. · Developing and implementing computationally intensive algorithms using high-performance computing (HPC) clusters. · Managing and analyzing multiple large-scale datasets, including UK Biobank (UKBB
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. Develop algorithms to identify specific seabed characteristics. Conduct independent research related to underwater active acoustics and seabed sensing. Collaborate with researchers from academia, industry
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, including prediabetes, type 1 and 2 diabetes, and non-alcoholic fatty liver disease (NAFLD). Their research informs artificial pancreas algorithms and contributes to drug development targeting hepatic
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Equation, Stochastic simulation algorithms, and approximation methods. ● Experience with single-cell or spatial transcriptomic data analysis. ● Familiarity with machine learning and deep learning