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/deploying deep learning models and machine learning applications. Computer skills: Python (PyTorch, TensorFlow), databases (MySQL), 3D Slicer, ITK-SNAP, OpenCarp. Previous experience in research activity in
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dedicate 37.5 hours per week / 100% full-time to the SMART-CM project. To be admitted to this selection process, it is mandatory to submit your application to the call for applications published at UC3M
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schedule. Selection process How to apply: Interested candidates must send their applications to odriva [at] pa.uc3m.es, indicating in the email subject the reference “ROCINANTE-Px” (with x=1,2) and attaching
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to present research activities. Flexible working environment and schedule. Selection process Interested candidates must send their applications to odriva [at] pa.uc3m.es, indicating in the email subject the
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of theproject: 1. Initial coordination of the project 2. Optimization of the bed receiver using AI from the data already available. This consists of the operation of the bed under direct and indirect mode, using
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, including beam-steering techniques, full-duplex operation, and self-interference mitigation. The project will explore innovative solutions using metasurfaces, multilayer structures, and advanced feeding