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position in big data analysis, substance use, neurocognition, and tobacco regulatory science. The position entails research on (1) analysis of big data using advanced statistical methods, (2) assessment
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 10 hours ago
, or a related field. Preferred Qualifications, Competencies, and Experience Coding and statistical analysis experience is preferred. Special Physical/Mental Requirements Special Instructions
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Access (OEA) at (631) 632-6280 or visit OEA . In accordance with the Title II Crime Awareness and Security Act a copy of our crime statistics can be viewed here . Visit our WHY WORK HERE page
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guidance from expert PET researchers and statistical support (from the Biostatistical Consulting Core). In addition, the candidate will have access to numerous internal funding mechanisms to obtain funding
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health; funded by the National Institutes of Health and the Centers for Disease Control and Prevention. The post-doctoral associate will provide expertise in statistical analyses and assist with
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project funds are secured and from a non-federal source. The position involves applying bioinformatic and statistical tools to existing multidimensional datasets, including metagenomic, transcriptomic
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electronic health records (EHRs) from multiple UK hospital centres using advanced data analytics including machine learning, deep learning, and statistical techniques—with a particular emphasis on deep
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corresponding scientific project management is desirable Confident in independent bioinformatic and statistical analysis of high-throughput sequencing data Experience in working with biofilms is desirable
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master's degree (or equivalent) and PhD in Mathematics/Statistics/Data Science Research expertise in the analysis of complex systems Familiar with network analysis, concepts of resilience (e.g. adaptive
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to join our team. Our lab focuses on developing and applying innovative statistical machine learning methods, single-cell multi-omics, and systems immunology approaches to investigate immune-mediated