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opportunity without regard to an individual's age, color, disability, gender, gender expression, gender identity, genetic information, national origin, race, religion, (including pregnancy and pregnancy related
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experimental procedures. Data preparation for oral presentations, grant applications and publication in professional journals. Implementation of bioinformatics approaches. Conformance to standards of responsible
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are diverse; with exciting ongoing grant-funded and pre- funded projects that include big-data, population health studies, mental health aspects of head and neck cancer outcomes, human papillomavirus (HPV), HPV
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, gender identity, genetic information, national origin, race, religion, sex, sexual orientation, or veteran status. Duke aspires to create a community built on collaboration, innovation, creativity, and
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. Postdoctoral Associate in Developing Methods to Improve Efficiency and Robustness of Clinical Trials Using Historical Controls and Real-World Data DESCRIPTION Duke University and North Carolina State University
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27710, United States of America [map ] Subject Areas: Statistics / Statistics Biostatistics / Biostatistics and Data Science Data Science / Machine Learning Appl Deadline: none (posted 2025/02/12
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DESCRIPTION Duke University and North Carolina State University (NC State) invite applications for a full-time Postdoc Associate to conduct research on causal inference and analytic methods for data integration
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, including literature review, experimental design, data analysis, collaboration, and dissemination of findings through conferences and publications. Apply for fellowships and awards, and provide mentorship
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. To Apply: Please submit (1) a Cover letter that includes your contact information, why you are interested in this position, relevant experience and qualifications for the position, and your ideal start date
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opportunity to develop innovative statistical methods in clinical trial design and variable selection methods in high dimensional data that will predict clinical outcomes and meta-analyses. The successful