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disparities across the prevention and survivorship continuum. Our work leverages large-scale cohort studies, registry data, and multi-omics platforms to generate actionable, high-impact insights. The team
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national scientific meetings Compile data and communicate findings through research manuscripts Choose Duke. Join our award-winning team as identified by Forbes magazine as America’s Best Large Employer 2024
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outcomes. • Prepare manuscripts, abstracts, and presentations for scientific dissemination. • Maintain accurate documentation of scientific data, methods, and results. Definition & Expectations
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data collection activities, ability and interest in working with large datasets, and interest in working with interdisciplinary teams of researchers. The expectation is that the scholar would help lead
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investigations including planning, development, and implementation of experimental procedures as well as data analysis under supervision of senior scientists to contribute to research projects in the Tisch Brain
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addition to pursuing their own research agenda, we seek applicants with experience in survey design and computational methods, and working with complex large-scale data. Successful candidates will have completed a Ph.D
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computing, machine learning for hardware design, integrated circuit design, or hardware–software co-design. Experience with semiconductor design tools, circuit/system modeling, or large-scale hardware design projects
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requires working with large data sets related to parenting and child development across multiple sites in the United States, helping to prepare data and estimate models for a variety of research papers, and
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behavioral clinical trials focused on pain, symptom management, and health promotion in patients with cancer and other chronic diseases. Current projects range from pilot studies to large trials, including
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, bioinformatics, or a related discipline. The successful candidate will lead computational research projects applying advanced statistical, machine learning, and artificial intelligence approaches to large-scale