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YOUNG RESEARCHER IN THE FIELD OF EARLY DETECTION OF THE HEALTH STATUS OF PLANTS USING REMOTE SENSING
performance under different acquisition conditions and across different types of plant communities, programming and automating analytical workflows in Python and R, and integrating these workflows with
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multiple access. The focus will be on the application of AI techniques, aiming at their reliable, robust, and effective integration. Requirements: - Experience with the Python programming language
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. Preferred Qualifications Bachelor?s degree in Physics. Other Requirements Experience with Python, C++ and Root. Excellent written, verbal, and interpersonal communication skills. Ability to maintain high
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, including FEM and structural analysis. Experience or interest in metamaterials, fracture mechanics, or advanced material behavior. Programming skills (e.g., Python, MATLAB, Julia,..), ideally with experience
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will require a strong interest in experimentation, reproducibility of results, and reading scientific papers. Good programming skills (in practice Python) are expected, as well as a genuine interest in
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at https://energyaccess.duke.edu/ . The scholar selected for this position will work closely with EAP faculty (including Profs. Marc Jeuland and Robyn Meeks) and with co-director Jonathan Phillips, as
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. Preference will be given to candidates proficient in design and development of a new optical instrumentation, FLIM, software development, especially with Java for ImageJ/Fiji, Python, LabVIEW, and MATLAB, and
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 43 minutes ago
inform observable macroscopic properties as part of the activities of the UNC Superfund Research Program (SRP) (https://sph.unc.edu/superfund-pages/srp/). This work involves running, developing, and
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Python and AI-enabled methods to extract, classify, and summarize insights from unstructured data, including text, images, and other digital content. This work will help BSA detect trends, measure impact
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. • Strong proficiency in Python and relevant libraries for data analysis and modelling (e.g., TensorFlow, Keras, Scikit-learn, Pandas); knowledge of R would be an asset. • Familiarity with geospatial data