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-engineering. A semantic interoperability backbone and data management are also required due to the large number of stakeholders and their need to receive or exchange information. Experience with modelling
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. You will join our large team of about 30 researchers that focuses on the molecular aspects of infection of corona-, influenza- and picornaviruses. We offer a challenging position in a dynamic and
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programming, statistics, machine learning and big data approaches in the context of soil-vegetation-atmosphere interactions excellent writing and oral communication skills in English and strong ambition
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National Growth Fund-funded research project ‘Re-Ge-NL Opens external : Accelerator for the transition to a regenerative, profitable and socially supported agricultural sector’ in which a large consortium
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a large interdisciplinary consortium of digital democracy researchers as well as several societal partners. The successful applicant is expected to carry out research on the algorithmic foundations
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expertise in data science, with hands-on experience in techniques such as machine learning, reinforcement learning, and simulations, and in handling large-scale, within-person, or real-time datasets; A strong
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image analysis (segmentation, statistical feature extraction etc.) The project is part of a larger collaboration involving the Faculties of the University of Twente and a large industrial company
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traditional large-sample approaches to study fewer individuals in unprecedented detail, leveraging an already collected rich dataset to better understand individual brain differences in autism. What are you
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’ sending and receiving regions. It uses big data and agent-based modelling to analyse the impact of those changing patterns of spatial mobility on EU regions and envisage policies to counterbalance
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delamination of TaC coating from the graphite substrate, which are mainly caused by the large thermal expansion mismatch between the coating and graphite substrate during chemical vapor deposition and during