14 computer-network "Computer Vision Center" Postdoctoral positions at Utrecht University
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! Research fields Communication sciences; Computer science Job types Postdoc Education level Doctorate Weekly hours 32—40 hours per week Salary indication €3706—€5760 per month Location Princetonplein 5
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Vision, the National Archive, and the National Library of the Netherlands. The research will take place in collaboration with the HAICu fieldlab ‘Deep Journalism’, which develops functionality for
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dimensions of NBS. This position centres on “Task 3.3 – Establish a Mediterranean NBS Community of Practice as a Social Innovation Network”. Building on insights from earlier translocal social
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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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approaches like network analysis and complementary systems-change-oriented methods to national-scale case studies, while supporting the development of pathways and theories of change; develop reproducible
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partners at Princess Maxima Center) using AI/ML techniques, implement antigen data analysis and discovery processes, and contribute to the maintenance of data infrastructure in collaboration with
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researcher with a strong technical background and an interest in societal impact. You have: Must have criteria: a PhD in computer science, artificial intelligence, data science, computational social science
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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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(e.g., GitHub); experience working with multi-source geospatial data (e.g., network, satellite); experience with GIS and GeoAI-related model development and evaluation; an interest in GIScience, health
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intelligence, computational biology, bioinformatics, computer science or a closely related field; • strong hands-on experience with deep learning and modern representation learning, preferably including