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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | 1 day ago
to misapprehensions about the outer planets and moons. In addition, many images were never processed in to full color and remain monochromatic. Digital image processing has now advanced significantly, permitting new
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of electron microscopy and beam-material interactions. The ideal candidate will have a basic understanding of image processing. Core competencies: – Knowledge of image processing software (Avizo, Dragonfly, etc
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processing for wireless communication systems including satellite communications and radar systems and is currently expanding its research activities in exploring several emerging use cases of next generation
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configurations hinders the creation of generalizable solutions for processing these images. This project proposes an innovative approach that combines state-of-the-art diffusion models with physical radar
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, imaging). • Solid foundations in signal processing and statistics. • Experience with machine learning for regression (e.g., tree-based methods, neural networks) • Hands-on experimental skills: ability and
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artifacts caused by atmospheric interference. Furthermore, the inherent complexity of different radar types and their specific configurations hinders the creation of generalizable solutions for processing
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Chair of Biological Imaging 02.02.2026, Academic staff We now seek a highly qualified and motivated Post-doctoral researcher (f/m/x) to drive the development of a novel quantum enhanced microscope
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the digital models into different simulation environments and to support the testing and training of medical robotic systems. The successful candidate should have a strong background in medical image analysis
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innovative employers in the region. With more than 6000 employees from 100 different countries, we are helping to build tomorrow's world every day. Through top scientific research, we push back boundaries and
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into operational decision‑support tools for farmers, in close collaboration with an industry partner. The project focuses on automated rumen‑fill assessment using 3D imaging, computer vision, and predictive