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accessibility), and clinical data. * Develop, apply, and benchmark machine learning and statistical models for subtype discovery, classification, and outcome prediction. * Contribute to the development
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The Nuclear Technologies and National Security Directorate (NTNS) is seeking a dynamic and passionate Postdoctoral Appointee with strong background in statistics or machine learning to lead an
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University of North Carolina Wilmington | Wilmington, North Carolina | United States | about 22 hours ago
access helps us provide an enriching learning environment for students, faculty and staff interested in the marine sciences. College Center for Marine Science - 306 College College/School Information
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in tropical regions; analyze links between macrofauna and soil carbon; build/validate scoring algorithms using machine learning/cumulative functions. Outputs – Lead scientific, technical, and policy
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Experience in plant breeding for resistance to biotic and/or abiotic stresses, programming, machine learning, and genomic data analysis. Desirable requirements 1. Cost-effectiveness assessment: rapid
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computational and machine learning approaches. What We Offer As an employer, we genuinely care about our employees’ wellbeing and this is reflected in the range of benefits that we offer including
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systems. • Develop and implement predictive models for packaging performance using machine learning approaches and physics-based simulations. • Investigate logistics optimization strategies for packaging
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partner who focuses on the underlying machine learning models, and you will help coordinate the joint work across the two teams. The position offers a strong publication trajectory at leading HCI venues
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 1 month ago
desirable. Candidates with experience in time-series machine learning, advanced data analytics, and programming (Python) are especially encouraged to apply. Special Physical/Mental Requirements Special
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, and computer vision. In particular, it focuses on the measurement of eye-gaze as a key window into cognition, integrating experimental, comparative, and computational approaches. We aim to move beyond