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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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. 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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scalable software and algorithms for genomic inference Collaborate with researchers across statistics, genetics, and computational biology Contribute to manuscripts, presentations, and open-source software
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advance pediatric, adolescent, and young adult cancer care using cutting-edge computational biology approaches. We strive to understand the germline genetics and tumor genomics of pediatric cancer to inform
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the cellular and molecular pathways disrupted in brain disorders such as schizophrenia and autism, by utilizing recent advances in genetics and genomics. We are developing and applying tools to understand how
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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
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neuroimmunology program in the Department of Neurology at Yale School of Medicine, with close ties to genetics, computational biology, and clinical trial groups, including partnerships with pharmaceutical