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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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will develop novel statistical and machine learning methods for any of the following: multi-omics data (such as bulk and large-scale single-cell RNA sequencing data, spatial transcriptomics, bulk and
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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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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
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epidemiology methods relevant to cancer and population health, especially for secondary data analysis; Develop advanced statistical methodology, causal inferences in observational data, quasi- experimental
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, you will focus on delivery methods for genome and epigenome editing tools. This will require expertise in molecular and cellular biology, molecular engineering, genetic manipulation, and bioinformatics
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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 candidate will collaborate
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, mood disorder models, or equivalent. The candidate should also have proficiency in some surgical neural targeting method. Programming skills and an understanding of mouse genetics are also a plus. The
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studies of fetal ultrasonic imaging methods. The applicant should have experience in programming diagnostic ultrasonic scanners, advanced programming and mathematical skills, and knowledge of ultrasonic
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animal species, generating standardized data that works effectively across diverse languages and cultural contexts while eliminating traditional barriers of recall bias. These methods are being deployed in