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, and visiting scholars. Participate in the recovery, in vitro and greenhouse maintenance of transgenic switch grass plants. Participate in local and international travel. Provide data in a timely manner
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of processes through real-time data acquisition and analytics; Component fabrication (additive manufacturing); Characterisation (e.g. SEM, EDX, XRD, XPS, Raman spectroscopy, nanoindentation, AFM, etc.); And
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 20 hours ago
Posting Information Posting Details Department University Counsel - 200400 Posting Open Date 06/06/2025 Application Deadline 09/22/2025 Open Until Filled No Position Type Postdoctoral Scholar
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; phenotypic analysis and imaging. Keep organized analytical data of performed experiments and expected to report findings at lab meetings. Acts as a liaison/mentor to technicians, students and other laboratory
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provides robust learning experiences related to the science and application of HEOR, including cost studies, data analytics, economic models, real-world evidence, services utilization analysis, systematic
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ecology and management research, expertise in long-term ecological data analytics and modeling, and proficiency in statistical analysis are encouraged to apply. Preference will be given to candidates with
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the field of dermatology, leveraging epidemiology, data science, and public health to advance health equity. Leandra A. Barnes, MD is an NIH-funded K scholar committed to elucidating the underlying mechanisms
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also include technique development work aimed at combining imaging techniques and data analysis to provide a more integrated picture of life processes in the context of health and disease. To be a
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research in Statistics and the application of statistical methods to solve real-world problems in medicine and public health. The research will specifically involve developing innovative analytical methods
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large amount of data, using advanced statistical techniques and mathematical analyses. Manage analytical projects from data exploration, model building, performance evaluation, through implementation