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PhD student position on development of innovative bifunctional oxygen electrodes for SOC technology.
development of innovative SOC stacks gathering deep knowledge on electrochemical and structural characterization of energy technologies such as fuel cells and electrolyzers. Among the characterization
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UNIVERSIDAD CATÓLICA DE MURCIA - FUNDACIÓN UNIVERSITARIA SAN ANTONIO DE MURCIA | Spain | about 2 months 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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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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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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. 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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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