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UNIVERSIDAD CATÓLICA DE MURCIA - FUNDACIÓN UNIVERSITARIA SAN ANTONIO DE MURCIA | Spain | 28 days ago
. Through advanced Machine Learning and Deep Learning technologies, it seeks to automate agronomic processes, optimize resource use, and maximize production in a sustainable way. Main duties Design
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-year position dedicated to the project “Foundations for Adaptive and Generalizable Deep Learning” (EXPLORA), funded by Ministerio de Ciencia, Innovación y Universidades/AEI, focused on ‘Continual
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in MRI sequence programming, preferably using the Siemens IDEA platform, is a plus, particularly for projects involving sequence development. Experience applying deep learning techniques
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Machine Learning A PhD position is available at the Computer Vision Center (CVC) under the supervision of Fernando Vilariño and Paula García . The successful candidate will be enrolled in
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modulators of TDP-43 by conditional deep learning In ALS, TDP-43 is mainly in the cytoplasm with a loss of nuclear function and formation of toxic stress granules. Small molecules have been designed to avoid
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. Preliminary exposure to machine/deep learning, statistical modelling or generative AI. Application process: Interested candidates are invited to apply via the PHYNEST online platform by submitting a full CV, a
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generate, transmit, and detect OAM-entangled photons under realistic atmospheric turbulence. Deep learning algorithms will be employed to pre-compensate distortions in real time, maximizing state fidelity
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perform specialized fabrication and experimental tasks and develop a deep understanding of the theoretical framework and modeling tools. This will require communication skills, capacity to learn, and