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for a postdoctoral research position at Duke University in topic area of environmental geochemistry. The Postdoctoral Associate will lead a project on critical metals resourcing in mine wastes
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the laboratory manager and Principal Investigator. 6. Mining large sequencing data sets Department Specific Qualifications Education: PhD in Molecular Biology, Immunology, Physiology or related field Experience
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Posting Details Posting Details Logo Institution South Dakota Mines Working Title Postdoctoral Researcher Posting Number NFE02537P Department SDSMT-Nanoscience and Nanoengineering 1 Physical
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will join a multidisciplinary team to work on cutting-edge research projects to develop and apply data mining/machine learning approaches on high dimensional biological and clinical datasets. The initial
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Experience: Experience in advanced analytical theories, predictive modeling, data mining, and data extraction. Experience in clinical and health services research. Expertise in using various statistical
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moves. Success will be measured by having published or contributed to papers in top venues (e.g., Nature Science of Learning, Computers and Education, ACM Learning at Scale, Educational Data Mining) and
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, modeling and analysis, integrating diverse data sets to identify global risks affecting sourcing strategies. In this role you will: Conduct and contribute to research and model development to enhance
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-motivated and have strong oral/written communication skills. Preferred Qualifications: Previous experience with prostate cancer, epigenetics, bioinformatics data mining, and cancer xenograft mouse models is
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 4 hours ago
Posting Information Posting Details Department Neurology - 411801 Posting Open Date 05/16/2025 Application Deadline Open Until Filled Yes Position Type Postdoctoral Scholar Position Title Post-Doc
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, proteomics, lipidomics and metabolomics in large-scale human populations. The lab is interested in integrating and mining the different types of data to understand the genomic causes and other biomarkers as