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Field
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executing experiments, data analysis, laboratory record keeping, and oral and written presentation of experimental results. The research associate will be expected to work collaboratively with other staff
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, MOF synthesis, and analytical techniques such as: Nuclear Magnetic Resonance (NMR) Spectroscopy Infrared (IR) and Raman Spectroscopy Powder X-Ray Diffraction (PXRD) Preferred Skills Demonstrated ability
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located at 1100 South Marietta Parkway, Marietta, GA 30060. Department Information DEPARTMENT SPECIFIC TASKS AND RESPONSIBILITIES: 1. Conduct independent and collaborative research aligned with MOVE focus
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at 501-671-2219 or 479-502-9820. Department: FDSC | Protein Chemistry Department's Website: https://food-science.uark.edu/ Summary of Job Duties: The successful candidate will work in the Analytical
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Postdoctoral Associate Required Qualification: (as evidenced by an attached resume) PhD (or foreign equivalent) in Bioengineering, Genetics, Genomics, Biomedical Engineering, Analytical Chemistry
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wildlife data from the Chicago area. Use various analytical techniques to answer questions related to wildlife disease dynamics, genetics, social behavior, and general urban ecology of mammalian predators
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variety of scientific principles and theories. Maintains substantial knowledge of state-of-the-art principles and theories. Develops advanced analytical models and systems and provides solutions and
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laboratory techniques (mammalian and bacterial) Multi-omics data analysis CLSM and SEM imaging skills Strong analytical, problem-solving skills and Excellent written and verbal communication skills and ability
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National Aeronautics and Space Administration (NASA) | Fields Landing, California | United States | about 2 hours ago
to scientific data analysis. Development of secondary projects which foster collaborations with other researchers both at NASA Ames and externally is also encouraged. Field of Science: Earth Science Advisors
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implement MR-based simulation platforms for training and process enhancement in remote construction. Apply machine learning techniques for optimizing construction assembly processes, predictive analytics, and