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analyses, quantitative descriptive and association studies, complex systems analyses, automated extraction data analysis and methods-needs matching Your PhD position is part of the Academic Research Network
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will directly measure social network deficits across multiple migrant groups and enable systematic migrant-group comparisons. Supervision Team The project will be supervised by Verena Seibel and
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opportunity to explore neural network architectures, tabular transformers or Bayes methods to include process-information into machine learning and to develop new geoAI approaches for spatiotemporal mapping
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backward erosion (piping). Your job The Netherlands relies on a network of about 2,000 km of river dikes to contain flooding in its floodplains. These dikes undergo continuous assessment, maintenance
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burial of microplastics and POC in currents down submarine canyons; incorporate these mechanisms into an existing computer model for sediment flux through submarine canyons; and validate the model on
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mentality. We are looking for you, if you have: a (research) master’s degree in Artificial Intelligence, Computational Linguistics, NLP, Computer Science, Data Science, or a related field, with a strong
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engagement and participatory research with quantitative system modelling of our research group; experience with systems modeling and computer programming (e.g. Python); strong communication and scientific
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candidates with: An MSc degree in (or nearing completion of) an MSc program in Geoinformatics, Computer Science, (Quantitative) Geography, (Spatial / Geographic) Data Science, Environmental Science, or a
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pesticides and health. For the analyses of child cognition, you’ll be part of a team of researchers, including other (PhD) students and external collaborators involved in the OBO-2 project ( https
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burial of microplastics and POC in turbidity currents down submarine canyons; incorporate these mechanisms into an existing computer model for sediment flux through submarine canyons; and validate the