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Technical Director will oversee the daily operation of the PISR and its portfolio of advanced pre-clinical imaging technologies, including magnetic resonance imaging (MRI), micro-computed tomography (micro-CT
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imaging such as live cell imaging, total internal reflection fluorescence (TIRF) microscopy, FLIM, STED, lattice lightsheet microscopy, fluorescence correlation spectroscopy (FCS), image processing and
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Bigo-Simon (specialist in self-assembly, image processing and 3D structural reconstruction), Marc Schmutz (expert in cryo-TEM) and Jérôme Combet (specialist in X-ray diffraction). The postdoctoral
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: How do we watch material surfaces evolve? Change: Building a surface-sensitive diffractive microscope. Impact: Enabling high-resolution imaging of surfaces during operation. Job description We
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, and participating in the project's science outreach activities. The postdoctoral fellow will be responsible for developing study protocols using advanced imaging techniques. He or she will be involved
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electron optics, MEMS technology, experimental microscopy, and computational imaging, we aim to open new possibilities for high-resolution surface imaging at low electron energies. As the postdoctoral
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/Absorption Spectroscopy preferred). Demonstrated experience with high-speed imaging, data acquisition, and complex optical alignment using lasers and advanced detectors. Experience processing dense
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Science, Signal and Image Processing, Computer Vision, Geomatics, or a related field, with skills in: -Python and/or C++ programming; -Image processing, 3D geometry, or computer vision; -Processing and analysis
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of both macroscopic measurements (forces, torques) and internal fields obtained via tomographic imaging. The postdoctoral researcher will also be responsible for validating and evaluating the developed
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 10 days ago
Hill seeks a computational postdoctoral researcher to develop and apply methods for integrating single-cell sequencing and imaging data within controlled cell-line model systems. The project focuses