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Education & Experience: PhD in Computer Science, Visualization, Cartography, Geographic Information Science, or a closely related field. Strong background in visualization, computer graphics, or perceptual
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towards improving controllers in turbulent flows. On any given day, you may be called on to: Own and execute novel machine-learning workflows related to wind conditions and control performance. Post-process
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appointment is for one year, renewable for a second year pending satisfactory performance and availability of funding. Research topics of interest include numerical methods for scientific machine learning and
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materials modeling and mechanics, including molecular simulations, multiscale modeling, and/or machine‑learning‑based materials design Demonstrated publication record in peer‑reviewed journals relevant
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data science, and/or public health or related fields including health services research, health informatics, computer scienceExperience in data analysis using statistical software & machine learning (e.g
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sciences, including technologies that are driving the generation of massive datasets, the exponential growth of publicly available data, and revolutionary approaches in statistics, machine learning, and
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participant outcomes. The project will use a variety of approaches, including human perceptual experiments, machine learning, digital signal processing, and computational models of hearing. UConn has a vibrant
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, and mentor graduate and undergraduate students, and may also teach one course per year for the Department of Statistics. A Ph.D. in Statistics, Biostatistics, Machine Learning, or a directly related
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. The successful candidate will engage in innovative research addressing statistical methodology, machine learning, and/or learning techniques in complex biomedical and health-related challenges. We particularly
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work is studying how undergraduate STEM courses can be tailored to meet the needs of all learners. Current projects involve studying STEM instructor perceptions of student-centered learning as