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, measurement, and evaluation strategy, with a focus on cross-sector data infrastructure, linkage, performance measurement, evaluation, and continuous learning. Responsibilities: 1. Serve as a scientific partner
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addition to applicants’ prior accomplishments, we would like to learn what motivates them, how they approach unfamiliar problems, and what they hope to contribute to, and learn from, an interdisciplinary research
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. The Department of Neurobiology is looking for a highly motivated Postdoctoral Associate to join our team investigating the neural mechanisms of motor learning and long-term motor memory. In this role, you will
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Summary: Duke University is a world-renowned research institution. Currently, we are looking for a Postdoctoral Associate with expertise in deep learning to participate in a research program focused on
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. Knowledge of survival analysis. Knowledge of machine learning methods. Other Requirements Application materials must include: Curriculum Vitae (CV) Statement of research interests Names of three professional
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rapidly changing priorities and have ability to quickly learn new skills. Must be detail-oriented, well organized with strong communication skills and ability to work in an interactive team environment
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multidisciplinary team members and the broader scientific community. Contribute to a culture of innovation, collaboration, and continuous learning. Support Research Excellence Adhere to all institutional requirements
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learning Opportunity to support diverse and engaged student populations Innovative academic environment Comprehensive employee benefits and wellness resources Inclusive community that values diverse
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independent scientific reasoning and problem-solving Learn and apply new experimental technologies and methodologies Contribute to high-impact research advancing lung biology and disease understanding Choose
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, predictive modeling, machine learning, and causal inference methods. Experience with claims-based or EHR-based phenotyping, variable construction, treatment pattern analyses, healthcare utilization studies