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. Applicants should have, or defended the viva of, a PhD in computer science, artificial intelligence, medical image analysis, biomedical engineering, or a closely related discipline. We are particularly
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the Future of Agriculture If you want your work to move beyond the lab—from concept to prototype to real-world field deployment—while solving complex engineering challenges alongside leading agricultural
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application process here. About the position Are you motivated to develop next-generation research infrastructure at the intersection of robotics, mechatronics, sensor systems, and life science technology? We
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Processes (https://simap.grenoble-inp.fr ) - is a multidisciplinary laboratory with more than 200 participants from chemistry, physics, materials and fluid mechanics. It is one of the leading laboratories in
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 14 hours ago
cloning * Bioinformatics or computational analysis experience * Experience working with large imaging or omics datasets * Tissue culture and mammalian cell engineering * Cellular metabolism and stress
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requires detailed imaging, beyond what is currently possible in humans in vivo. In an NWO-funded Vici project, we leverage Ultra-High Field MRI to bring the cerebellar mesoscale into view. In this PhD
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research and teaching team in the field of image information engineering. The team’s work combines vision systems and computer vision, AI-based image data analysis, VR/XR technologies, and the integration
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Technologist acts as a subject matter expert and resource for mammography staff, radiologists, physicists, and leadership, promoting high standards of care, image quality, safety, and operational efficiency
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Massachusetts Institute of Technology | Cambridge, Massachusetts | United States | about 1 month ago
OCR and image processing applications; conduct quality control; and meet production goals and deadlines. The position collaborates with staff and vendors on digitization projects; applies appropriate
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qualifications: Master's degree in Engineering (M.Sc. Eng.) or equivalent. Experience in handling and processing medical images. Experience in computer programming. Preferred Qualifications Knowledge of 4D Flow