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Postdoc: Machine learning for wind flow prediction in coastal dunes Faculty: Faculty of Geosciences Department: Department of Physical Geography Hours per week: 36 to 40 Application deadline: 6
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Are you passionate about developing cutting-edge AI techniques to enhance interaction and communication across multiple modalities, such as text, pictures, audio, and video? Join the large scale
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)design; integrating multi-source datasets, including street-view imagery, GIS data, smartphone mobility data, and qualitative insights; applying and adapting state-of-the-art foundational AI and machine
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and communication across multiple modalities, such as text, pictures, audio, and video? Join the large scale HAICu project to help unlock the potential of cultural digital archives through multimodal
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together nine demonstration sites across the Mediterranean — from the Aegean Islands and Central Greece to Sardinia, Catania-Ferla, PACA, Aragón, Alentejo, İzmir, and Nicosia — to scale up nature-based
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design, train and implement ARCA: an AI foundation model for crop microbiomes. You will work at the interface of deep learning, bioinformatics and microbial ecology, using large-scale microbiome and genome
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, you will design, train and implement ARCA: an AI foundation model for crop microbiomes. You will work at the interface of deep learning, bioinformatics and microbial ecology, using large-scale
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scale. Besides PI’s Kraal and Wolthers, the PHOSFLUX team consists of a NIOZ-based PhD student performing experiments and analyses, and a UU-based postdoctoral researcher who focuses on modelling
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- 1.0 FTE) for 24 months; a working week of 32 - 40 hours and a gross monthly salary between €3.706 and €5.760 (salary scale 10 under the Collective Labour Agreement for Dutch Universities (CAO NU
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complementary systems-change-oriented methods to national-scale case studies, while supporting the development of pathways and theories of change; develop reproducible analytical tools, workflows and monitoring