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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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University of New Hampshire – Main Campus | New Boston, New Hampshire | United States | about 2 hours ago
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 New Hampshire – Main Campus | New Boston, New Hampshire | United States | about 1 hour ago
. 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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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
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-free algorithms for real-time optimization of turbine operating conditions (e.g., yaw set points). Other projects may be assigned by the supervisor depending on skills and technical needs. The successful
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are the following: Obtain and maintain regulatory approval. Set up screening algorithms to identify eligible participants. Recruit participants, collect/ process samples. Design data collection tools (e.g., redcap
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evaluation of machine learning, computer vision, and other algorithms, primarily in the context of health. They will be part of the thriving research community of Duke Spark (spark.duke.edu) where AI