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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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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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related to modelling (e.g. integrated assessment models, stock–flow consistent models, system dynamics, input–output analysis, econometrics, machine learning, material/energy flow analysis, etc.) Motivation
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programming Expertise in additional quantitative research methods (e.g. time-use analysis, system dynamics, machine learning, econometrics, advanced statistics, big data, material flows analysis, etc
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/ ). We are looking for a highly motivated, enthusiastic, empathic person, with passion for research and desire to learn and explore new technologies, aiming at significantly improving her or his