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, biologists, and data scientists. The emphasis will be on enabling high-fidelity image reconstructions from sparse and noisy data, leveraging state-of-the-art methods in compressed sensing, optimization, and
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scientists. The emphasis will be on enabling high-fidelity image reconstructions from sparse and noisy data, leveraging state-of-the-art methods in compressed sensing, optimization, and machine learning
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to contribute to a highly collaborative, international project developing open-source low-field MRI systems for neuroscience research; Have research experience in compressed sensing and/or multi-contrast image
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, biologists, and data scientists. The emphasis will be on enabling high-fidelity image reconstructions from sparse and noisy data, leveraging state-of-the-art methods in compressed sensing, optimization, and
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to: Developing advanced end-to-end systems for the enhancement, compression, storage, and display of CBCT and CT images acquired using low-radiation dose protocols, as well as MRI images obtained through fast
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developing innovative methods focused on enhancing the visual quality of Cone-Beam Computed Tomography (CBCT) and other medical imaging modalities, creating advanced compression techniques for efficient
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in the field of heat pumps and refrigeration systems Knowledge of English. Specific Requirements Modelling and Simulation of CO2 Refrigeration Systems based on liquid piston compression, validated with
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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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/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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University of California, San Francisco | San Francisco, California | United States | about 12 hours ago
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