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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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Biology (CBM) offers advice, technical support and training in advanced optical microscopy and image analysis, providing comprehensive support throughout the entire experimental process, from sample design
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faculty engages in fundamental and applied research and education in lasers, optical fibers, semiconductor and integrated photonic devices, nonlinear and quantum optics, imaging, sensing, and displays
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a Horizon Europe Pathfinder science-to-technology breakthrough, targeting a paradigm shift in fabricating a novel optically active crystal – rare-earth (RE) doped sapphire (REDS). The EIC-funded
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, instruments and equipment. In addition, we develop laboratory test setups and simulation tools in the areas of imaging detectors, optical communication and quantum communication. You are encouraged to visit
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Education Institutions. Preference factors: - Experience in spectroscopy and/or spectral or hyperspectral imaging (e.g., LIBS, Raman,XRF, HSI); - Development and integration of optical or optomechanical
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selected candidate will be involved in Cell morphology studies by fluorescence microscopy; Image cytometry; Processing and interpretation of acquired images. Where to apply E-mail adriana.ioan
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, alignment, operation and/or application of optical microscopy systems, Strong background in image analysis or similar scientific data analysis using Python or MATLAB, An interest in working in a
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 21 hours ago
areas of knowledge which will be useful will include biomedical optics, super resolution imaging, adaptive optics, label free microscopy, MATLAB, and/or preclinical studies. Special Physical/Mental
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project (funded by Fondazione Cariplo), which aims to develop an innovative measurement technique based on speckle pattern imaging and artificial intelligence for the detection of milk adulterants