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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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, 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
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beyond. To this end, we will use a multidisciplinary approach involving advanced machine learning techniques and top-of-the-line ultra-fast processing platforms to propose an innovative solution that will
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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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the data collected and measured in the project. This will include research on machine learning methods on multivariate (high-dimensional) data for the identification of regions of interest and the
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beyond. To this end, we will use a multidisciplinary approach involving advanced machine learning techniques and top-of-the-line ultra-fast processing platforms to propose an innovative solution that will
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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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in Computer, Data Sciences or a bachelor in Biosciences. PhD in bioinformatics, data sciences, machine learning or related areas. Experience: Previous experience on the use of machine learning and data
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, the position is most appropriate for recent master's graduates (or soon to graduate) in fields related to machine learning, computer science, material science or related disciplines with excellent academic
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Principal tasks and duties: Study of proposals and research work on Machine Learning and Deep Learning (ML/DL) techniques that are applicable to multiple tactical domains in cyber defence environments, with