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by working to develop novel algorithms on finite element method, isogeometric analysis, geometric modeling, machine learning and digital twins to study various applications such as computational
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candidate will investigate new algorithms and models to develop, implement, and test multimodal machine learning algorithms to analyze and recognize multimodal human behavior in real world settings. Specific
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at the intersection of computation and life sciences. We are seeking a Research Associate. The position will perform statistical modeling of single-cell multiome data; development of algorithms to link enhancers with
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troubleshooting to ensure real-world readiness. Develop and implement algorithms for autonomous control, SLAM and navigation. Ensure reliable communication between hardware components and the robotic system
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troubleshooting to ensure real-world readiness. Develop and implement algorithms for autonomous control, SLAM and navigation. Ensure reliable communication between hardware components and the robotic system
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experience from which comparable knowledge is demonstrated may be considered. Preferred Qualifications Ph.D. degree. Demonstrated expertise in computational biophysics and molecular dynamics (algorithms and
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collected and writing up experiment results in the field of computational biology. Core responsibilities include: Working with biological data - implementing algorithms, programming and data analysis
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research applications based on knowledge of the theoretical foundations of information and computation including algorithms and data structures, and the application of state-of-the-art programming
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dynamics (algorithms and current practice). Experience in AI/ML. Experience in application performance optimization. Familiarity with parallel programming models (e.g., OpenMP, MPI, CUDA). Experience
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experience from which comparable knowledge is demonstrated may be considered. Preferred Qualifications Ph.D. degree. Demonstrated expertise in computational biophysics and molecular dynamics (algorithms and