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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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/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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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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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