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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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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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)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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-based web interface; publishing high-quality scientific articles in international journals; presenting findings at conferences and stakeholder events; contributing to supervision of MSc students. Your
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for subsurface water storage systems. Your main case-study area are the islands of Zeeland and Zeeuws-Vlaanderen, with connections to monitoring and pilot sites. You will work at the interface of hydrogeology
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for reasoning, on efficient and explainable machine learning for extracting and structuring information from large datasets, and on combining the two in neuro-symbolic AI.
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facilities and access to microscopes etc. The BioMS group is world-renown for mass spectrometry-based proteomics and structural biology, and applies these technologies to study amongst others cancer, auto
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facilities and access to microscopes etc. The BioMS group is world-renown for mass spectrometry-based proteomics and structural biology, and applies these technologies to study amongst others cancer, auto
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postdoc candidate, with a keen interest in academic and professional development, who meets the following requirements: a PhD degree in computer science or artificial intelligence; demonstrable machine