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Postdoctoral Research Associate to join our research group working at the intersection of advanced manufacturing, computational modeling, and machine learning. This position offers an opportunity to contribute
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independent research on the design and fabrication of neuromodulation devices and the characterization of these devices. Collaborate with lab members to test devices in cell culture and animal model studies
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Address Tucson, AZ USA Position Highlights The Lunar & Planetary Laboratory at the University of Arizona has an opening for a Postdoctoral Research Associate I in the field of modeling of planetary
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and cellular biology projects, using state-of-the-art instrumentation and in close collaboration with expert labs in biophysics, cell biology, and disease modeling. MINIMUM REQUIREMENTS Education
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solutions and have the opporutnity to contribute to world-class research, we encourage you to apply! Opporuntities to Contribute Develops dynamic river-lake network models to track the geochemical and
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 14 days ago
models is highly desirable. Create a Job Match for Similar Jobs About The University of North Carolina at Chapel Hill Carolina rates among the nation’s great institutions of higher education, set
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SPECIFICS Postdoctoral Researcher in Defect Modeling The Pennsylvania State University Department of Nuclear Engineering The Computational Nuclear Materials Group (https://sites.psu.edu/cnmg/ ) at Penn State
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Posting Title Postdoctoral Researcher: Modeling and Stability Analysis for Modern Power Systems . Location CO - Golden . Position Type Postdoc (Fixed Term) . Hours Per Week 40 . Working at NREL
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at Michigan Tech. The work will focus on building advanced reservoir simulation models coupled with geomechanics, performing risk assessments using NRAP tools, and contributing to leakage risk quantification
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productivity over time Fit structural equation models to test the effects of remotely sensed biodiversity (from hyperspectral and LiDAR) on forest productivity across three forest types (evergreen, deciduous