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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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seeking candidates with a PhD degree and expertise in an area pertinent to the project and experience in: Machine/deep learning algorithms Biomedical informatics Computer Science Expertise
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Programme? European Union / Next Generation EU Reference Number CEX2021-001202-M Is the Job related to staff position within a Research Infrastructure? No Offer Description Develop and train machine learning
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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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for anonymization and preparation of medical data for analysis, training, deployment and monitoring of novel machine learning-based tools on remote devices and providing support, in general, for the software
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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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PhD degree and expertise in an area pertinent to the project and experience in: ‐ Machine/deep learning algorithms ‐ Biomedical informatics ‐ Computer Science - Expertise on the implementation and
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, provisioning systems, input–output analysis, system dynamics, machine learning, and/or material flow analysis is desirable. Experience with existing ecological macroeconomic models (e.g. PyMedeas, EuroGreen
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++, Python and/or Matlab. Experience in Rendering techniques and/or Machine Learning is highly valued. Experience with Monte Carlo methods is also a plus. Work Environment The work will be developed within
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assess and tackle policy challenges. The expansion and improvement of the observer programmes and the advances in electronic monitoring and automated machine learning systems will enable species-specific