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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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Location of Position (City) Rapid City Posting Text The Arbegast Materials Processing and Joining (AMP) Laboratory at South Dakota Mines invites applications for a Postdoctoral Researcher. This is a full
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Postdoctoral position Posting Date: 7/29/2024 Yale School of Medicine Department of Emergency Medicine The Data Mining (DM) Lab at Yale University lead by Dr. Samah Fodeh has an opening for a
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Experience with machine learning, data mining and data assimilation is a plus Knowledge of git, docker, kubernetes, and/or metadata is a plus Ability to work within a team Excellent interpersonal and
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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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, conduct interviews and deploy surveys, analyze the interview and survey data, write up and present results at conferences and workshops. Quantitative position. The Post-Doc will help frame research
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Location of Position (City) Rapid City Posting Text The Nanoscience & Biomedical Engineering Department at South Dakota Mines invites applications for a Postdoctoral Researcher position within Dr. Shan
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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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performed by graduate students, and mining existing data sets that will contribute to the body of knowledge in asphalt materials. • Write technical reports that summarize multi-faceted research projects
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weather instrumentation data analysis (lidar, radar, weather station, radiometer, sonde, cameras) Experience with mining and cleaning “big” observational data and/or online databases Experience with