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PhD position: Global soil mapping with process-informed machine learning Faculty: Faculty of Geosciences Department: Department of Physical Geography Hours per week: 36 to 40 Application deadline
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cultural analysis; contributing to the development of a theory of the queer intellectual in close collaboration with the research team (including the PI and the Postdoc); producing a PhD dissertation, as
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participation of citizens. You will focus on developing adaptive learning systems that enhance the transparency and contestability of AI decisions through personalized, multimodal explanations. Your job AI is
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empirical and analytical quality in close collaboration with the PI and the Postdoc; Publishing in leading international peer-reviewed journals and contributing to edited volumes or other publications where
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, including abstract geospatial workflows; design AI- and machine-learning-based methods that automatically describe and model geodata sources using textual metadata (NLP) and the geodata itself; contribute
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excellent academic record and demonstrate proven enthusiasm for academic research. You are familiar with qualitative research methods (ethnography, in-depth interviewing). Candidates willing to learn
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to acquire and develop reflexive, participatory and transdisciplinary research skills. You will be part of a vibrant and supportive interdisciplinary, international community at the Copernicus Institute
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and democratic participation of citizens. You will focus on developing adaptive learning systems that enhance the transparency and contestability of AI decisions through personalized, multimodal