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work with Prof. M. Ángeles Serrano and Prof. Marián Boguñá at the interface between Network Science and Machine Learning. The goal is to merge the best of the two worlds to produce a new generation of
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from in vivo Raman spectra • Applying chemometrics methods to machine learning models • Simulations and modification of data • Carrying out Raman measurements in vitro and in vivo • Development
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to machine learning models • Simulations and modification of data • Carrying out Raman measurements in vitro and in vivo • Development of protocols for biocompatibility and strict compliance with regulations
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C++, Pytorch Al menos 3 años de experiencia en Visión por Computador y en Machine Learning/At least 3 years of experience in Computer Vision and in Machine Learning Specific Requirements Al menos 3
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decentralized machine learning environments. Blockchain technologies will also be used. - Collaboration in the dissemination of the results obtained in prestigious international forums." Requirements Research
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decentralized machine learning environments. Blockchain technologies will also be used. - Collaboration in the dissemination of the results obtained in prestigious international forums." Requirements Research
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Tensorflow.- High level knowledge of fluid mechanics, machine learning and modal decomposition algorithms. - High level knowledge of data analysis algorithms in fluid mechanics. - High level knowledge
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, it is essential to have effective multimedia security and cybersecurity measures. Responsibilities: In this role, you will combine research on watermarks and machine learning to develop novel
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research in Computer Vision and Machine Learning and the potential applications to Biometrics, Explainability, Security, and Media Forensics (among others)? If so, we have the perfect opportunity for you! We
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, risk management and machine learning. GREF brings together faculty from the departments of Economics and Finance, graduate students and a diverse network of collaborators, with the aim to facilitate