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/id_offre/133212 Requirements Specific Requirements Le/la candidat(e) devra posséder : — Une solide formation en mathématiques appliquées, incluant le traitement du signal et/ou des images. — Une bonne
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redundant pixels from one image to another, i.e. if the pixel has not changed it is not stored after compression. Therefore, the scenario until now has been that redundant information is unnecessarily
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The University of British Columbia (UBC) | Vancouver UBC, British Columbia | Canada | about 1 month ago
methods focused on enhancing the visual quality of Cone-Beam Computed Tomography (CBCT) and other medical imaging modalities, creating advanced compression techniques for efficient storage, designing high
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environment in the School of Physical Sciences. Maintain cell cultures and perform imaging studies and analysis on these cultures. About You Essential: A PhD in physics, biology, applied mathematics, computing
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of the identified structures via stereolithographic, 3D printing and textile techniques like tufting, machine-based embroidery techniques or non-interlaced 3D pre-forming. Development of advanced imaging and
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sampling. Responsibilities also include entering data to digital formats, taking plot photos, and uploading all data and images to a shared folder for subsequent analysis in ARM or JMP software. (25%) 3
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 6 hours ago
accompanying text about the artwork. To save your presentation file to send: File > “Compress Pictures”> Presentation (150 ppi) Save the PowerPoint presentation as a PDF. This allows us to see your images in
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CS Enterprise Imaging Full Time 86076BR Job Summary This position will work onsite several days per week in various San Francisco locations. Applies skills as a seasoned clinical applications
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research; Have research experience in compressed sensing and/or multi-contrast image reconstruction, and are keen to push the boundaries of what is possible with affordable imaging platforms. For informal
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, robustness, and informed model selection for target applications; Apply model compression techniques to encapsulate models for efficient inference on mobile and edge devices. Collaboration and Maintenance