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Field
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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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models. Familiarity with cloud computing environments (AWS, Azure) and AI, machine learning, or NLP tools applied to biomedical data analysis. LanguagesENGLISHLevelExcellent LanguagesCATALANLevelExcellent
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research institute at the University of Girona focused on computer vision and robotics. It combines fundamental and applied research in areas such as underwater robotics, medical image analysis, and
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apply machine learning algorithms with special attention to digital footprint reduction and data privacy. Functions to be developed: Develop methodologies and experiments to measure and optimize
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integration of the project webpage into the institutional platform Uso de machine learning para estimar propiedades geomecánicas del terreno a partir de datos de laboratorio/ Use of machine learning to estimate
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“Heterogeneous Advances in Machine Imitation Learning for Training Orchestrated Navigation (Hamilton)” The CVC offers one pre-doctoral fellowship linked to the project “Heterogeneous Advances in Machine Imitation
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resonance imaging) Fluency in English Experience and knowledge: Required: Experience in computer programming Expertise in Python programming for Machine and Deep Learning, e.g., sklearn, pytorch, tensorflow
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implementation of artificial intelligence models (machine learning, deep learning, and adaptive learning) applied to the sensorimotor control of a bionic arm prosthesis. • Advanced processing of neural (EEG) and
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statistics (regression methods, time series analysis, multivariate analysis, clustering methods), machine learning techniques (neural networks, random forests, decision trees, SVMs, etc.) and optimisation
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collaborative and international projects Experience/knowledge in HIL systems Hands-on lab experience and/or interest Knowledge on Machine Learning, or other AI techniques Team Worker Initiative in Research and