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predictive modelling; Bioinformatics and Knowledge Graphs (visualization and reporting); AI-based data integration across cohorts (with federated machine learning); Contribute to ongoing projects, such as: o
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: Ability to work in a team and maintain code cooperatively. Specific Requirements Knowledge: Efficiency and optimization algorithms for multivariable decision making. Statistics. Machine Learning
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to develop and implement machine learning/deep learning tools for personalized medicine in cancer by exploiting electronic medical records and medical images in relation to cancer diagnosis and the
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multidisciplinary team spanning hydrology, machine learning, ecological flows, and water resources management.The selected candidate will join the IberianCAMELS research team as a Predoctoral Researcher, contributing
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: Machine and Deep learning. In health and rehabilitation projects. Experience in functions similar to those described will be valued, specifically in the development of research activities, both in
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measurements. Professional Experience: In health and rehabilitation projects. Classification and models of Artificial Intelligence: Machine and Deep Learning. In recording and signal processing. Experience in
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to facilitate perceptual learning of different stimulation patterns; and (iii) the development of advanced AI algorithms capable of converting camera input into real-time electrical stimulation parameters. In
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. SILEX 2025) to calculate the Fire Radiative Power (FRP) and compare with satellite observations (VIIRS, SLSTR, FCI). Develop a fire front segmentation algorithm using machine learning techniques (deep
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processing (computer vision & machine learning) Where to apply Website https://sede.uvigo.gal/public/catalog-detail/28364578 Requirements Research FieldEngineering » OtherEducation LevelMaster Degree
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the LAMP group at the Computer Vision Center (CVC), in Barcelona, Spain. The position is for 2-3 years and linked to the project “Foundations for Adaptive and Generalizable Deep Learning” (EXPLORA