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, or related areas; Hands-on experience with, or a strong interest in, bioinformatics programming, including Linux, scripting, and R; Expertise in data mining and cleaning; Experience with the analysis
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in Trondheim. At NTNU, 9,000 employees and 43,000 students work to create knowledge for a better world. You can find more information about working at NTNU and the application process here . ... (Video
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other public events. Required Qualifications: Ph.D. in computer science, physics, data science, or closely related field; Experience in data mining and machine learning, or experience with agent-based
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information about AbbVie, please visit us atwww.abbvie.com . Follow @abbvie onX ,Facebook ,Instagram ,YouTube ,LinkedIn andTik Tok . Job Description Program Overview AbbVie needs outstanding individuals willing
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seabed mining, fisheries and submarine cables. CIL researchers go on to a variety of positions in government, academia and international organizations. For more information on the OLP’s team’s research
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, spatial transcriptomics, and high-plex immunofluorescence spatial proteomics to uncover disease mechanisms. Perform data mining, integration, and visualization, extracting meaningful insights from diverse
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Bioinformatics, Computational Biology, or related areas; Hands-on experience with, or a strong interest in, bioinformatics programming, including Linux, scripting, and R; Expertise in data mining and cleaning
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: Surface and materials science Microanalysis & mass spectrometry Isotope geochemistry and geochronology Mineral processing and engineering We enable critical research across sectors including mining and
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datasets. Experience with 3D data visualization programs. Knowledge of programming and software development. First-hand industry experience in mining, exploration, GIS, petrophysics or geophysics Why JCU
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University of North Carolina at Charlotte | Charlotte, North Carolina | United States | about 23 hours ago
focus of your research will be on mining publicly available data repositories and use machine learning to discover linkages between heterogeneous biological, social, and environmental data and human