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have: Expertise in processing optical remote sensing data over large areas and using machine learning models for predicting ecological metrics Strong background in remote sensing in hyperspectral imaging
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. in Computational/Applied Mathematics or Computer Science. Degree must have been earned within 72 months prior to beginning of appointment. Required Experience Desirable Education and/or Experience
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measure success. Basic Qualifications: A PhD in Materials Science and Engineering or a related field completed within the last 5 years Preferred Qualifications: Strong background in computational and image
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microenvironment. The project will employ genetically engineered mouse and human glioma models, along with advanced imaging techniques, single-cell and spatial transcriptomics, and molecular biology approaches
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normal and pathological feeding and reward processes. Applicant must hold a PhD or equivalent degree in neuroscience, biochemistry, molecular biology, psychology, computer science, biomedical engineering
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Apply Now Job ID JR101897Date posted 07/07/2025 The Condensed Matter Physics and Materials Science Division (CMPMSD)at Brookhaven National Laboratory conducts a wide-ranging research program
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | 2 months ago
Postdoctoral Program website for application instructions and requirements: How to Apply | NASA Postdoctoral Program (orau.org) A complete application to the NASA Postdoctoral Program includes: Research proposal
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to sufficiently perform the job duties. Must be computer literate with proficiency and working knowledge of database and reporting tools such as Microsoft Word, Excel, and PowerPoint. Must have the
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 22 hours ago
the Joint Department of Biomedical Engineering Department, based at UNC Chapel Hill. This research position will lead research in advanced ultrasound imaging technologies. Potential projects include super
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management and coding, machine learning AI, and familiarity with LSST data management image reduction and analysis tools. Familiarity with processing data at the DOE US Data Facility at SLAC National