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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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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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. Among the key duties of this position are the following: Conducts research processes and procedures in the PI laboratory. Assists in the acquisition and analysis of data. Supports PI's plans, developments
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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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molecular biology and cancer biology, required. ABD candidates may be considered; qualified candidates must be in the process of completing or have finished the training for Ph.D. and/or M.D. Candidates must
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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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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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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
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: Writing sample Sample of R or Stata computer code Regional Campus Rutgers Biomedical and Health Sciences (RBHS) Home Location Campus Piscataway (RBHS) City Piscataway State NJ Location Details Pre
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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