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eligibility, please visit: http://uhr.rutgers.edu/benefits/benefits-overview . Posting Summary The Department of Physics and Astronomy at Rutgers University invites applications for a postdoctoral research
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discipline, with experience in field methods and/or environmental data analysis; familiarity with Python-based workflows, AI/ML, or hydrogeophysical modeling is highly desirable. The position offers
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the Postdoctoral Associate or by others in the research group, by collaborators in other groups or from publicly available datasets. The project may also involve use and development of software programs for analysis
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data analysis, community-engaged science, grant development, and academic career advancement. Position Status Full Time Posting Number 26FA0605 Posting Open Date 06/12/2026 Posting Close Date
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have experience working with human subjects. Experience in multimodal data integration and statistical analysis is required. Experience with neuroimaging and/or other large-scale biomedical or behavioral
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have experience working with human subjects. Experience in multimodal data integration and statistical analysis is required. Experience with neuroimaging and/or other large-scale biomedical or behavioral
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have experience working with human subjects. Experience in multimodal data integration and statistical analysis is required. Experience with neuroimaging and/or other large-scale biomedical or behavioral
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, quantitative image analysis, rheology, and bioconjugate chemistry is preferred. The individual will report directly to the Principal Investigator. The candidate will be expected to contribute original research
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the analysis of large, integrated health-related clinical and administrative datasets, national surveys, and other data. Statement Posting Details Special Instructions to Applicants Quick Link to Posting https
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. Proficiency in R (+SAS or Python a plus), and experience working with quantitative data analysis and comprehensive understanding of statistical concepts and methods are essential. Certifications/Licenses