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computer programming experience in python or Matlab and the ability to deal with large, complex datasets are required. Experience with preparation and writing of scientific manuscripts and grant applications
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to evaluate multiple climate and climate change impacts across sectors such as sea-level rise/coastal processes, urban heat and health, or agricultural impacts. This position offers the candidate opportunity
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Qualifications Experience in quantitative modeling, stock assessment, population dynamics, statistics, and computer programming (R, Python, Matlab, Template Model Builder, AD Model Builder) are preferred
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Qualifications Experience in quantitative modeling, stock assessment, population dynamics, statistics, and computer programming (R, Python, Matlab, Template Model Builder, AD Model Builder) are preferred
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will also be considered. Experience with electronic health records, physiological signal processing, or predictive analytics in healthcare. Certifications/Licenses Required Knowledge, Skills, and
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various genomic datasets Effective spoken and written English required. High level of computer literacy required. Preferred Qualifications In-depth understanding and hands-on experience in RNA-seq and ChIP
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of the mechanisms by which environmental and occupational chemical exposures impact human health. Identify and measure human environmental and occupational exposures to chemicals. Treat populations adversely affected
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including data from parent surveys, child assessments, and classroom/teacher assessments. Performs both quantitative research including administrative data analysis. Supports processes to seek out funding and
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duties. Must be computer literate with proficiency and working knowledge of database and reporting tools such as Microsoft Word, Excel, and PowerPoint. Must have the ability to work collaboratively and
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undergraduate or graduate students, if appropriate. Additional Information The ideal candidate should be an independent, solution-oriented thinker with a strong background in processing very large data sets