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, including development of new computational tools for processing large-scale biospecimen data Creation of novel machine learning frameworks for automated scientific analysis and discovery Design and
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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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statistical models to investigate gene by environment interactions and to utilize bioinformatics resources and high-dimensional –omics data to elucidate the biological significance of the statistical analysis
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, United States of America [map ] Subject Areas: Climate Science Atmospheric Sciences Quantitative Analysis Appl Deadline: (posted 2025/05/12, listed until 2025/06/23) Position Description: Apply Today is the last day you can
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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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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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. The Postdoctoral Associate will apply his/her technical skills toward development and implementation of machine learning, computer vision, and other algorithms for analysis of medical images and prognostication as
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will involve analyzing patient data and coordinating analysis of patient samples. In addition to a copy of their resume, applicants are encouraged to submit a cover letter detailing their interests and
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. Responsibilities/Duties: · Perform biostatistics and bioinformatics for scRNA seq analysis. · Perform molecular, cellular, biochemical and immunological analyses · Optimize and troubleshoot experimental protocols
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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