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Health or other related disciplines with at least 2 years of post-bachelor's work experience. Previous work experience in big data analysis, managing large databases of multiple research projects relating
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Job Description Apply now Req Id: 37408 Job Title: Post Doc Research Associate City: West Lafayette Job Description: Job Summary Generate large genome-scale datasets with a variety of techniques
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Post-Doctoral Associate in Sand Hazards and Opportunities for Resilience, Energy, and Sustainability
Geotechnical Engineering, Civil Engineering, or a related field, and should demonstrate strong expertise in at least two of the following areas: Large-deformation numerical modeling (e.g., Coupled Eulerian
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molecular biology, microbiology, biochemistry techniques in the area of Salmonella biology and pathogenesis. Managing large data sets, synthesizing and integrating different types of data to come to
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data storage capacity to accelerate research in intensive computing and large-scale data analytics, commonly referred to as Big Data. This characteristic distinguishes the HPC center at the university
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starting June 1, 2025. Dr. Daisy Dai, Associate Dean for Research, is currently offering an NIH-funded postdoctoral position in big data analysis, substance use, neurocognition, and tobacco regulatory
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model fairness and model generalizability across multi-institutional electronic health records databases. The researcher will have access to the real-world EHR data from almost 20 sites across
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of computer simulation models that are open for reuse by health researchers and the NHS. The post holder will conduct cutting edge research that builds on our preliminary research with Open Weight Local Large
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University of Pennsylvania, Statistics and Data Science Position ID: 3334 -POSTDOC [#25722] Position Title: Position Type: Postdoctoral Position Location: Philadelphia, Pennsylvania 19146
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on collating and analyzing the large volumes of carbon cycle data gathered from the site to date, then preparing the resulting analyses for publication in scientific journals. Likely topics for papers include