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the fundamental understanding of pesticide residues in soils through experimentation, modelling, and big data analysis. You will: Combine existing farm management, soil property and soil pesticide residue data
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knowledge graph models of such transformations that are self-describing when applied to existing map repositories, and can be scaled up to large data repositories using state-of-the-art AI methods. In
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knowledge of extracting (event) data from text, documents, and/or media articles or implementing large-N analytics and algorithms, preferably LLMs and/or NLP. Conduct collaborative and independent research
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-engineering. A semantic interoperability backbone and data management are also required due to the large number of stakeholders and their need to receive or exchange information. Experience with modelling
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. You will join our large team of about 30 researchers that focuses on the molecular aspects of infection of corona-, influenza- and picornaviruses. We offer a challenging position in a dynamic and
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the interdisciplinary research programme GroenvermogenNL, which supports the large-scale development and implementation of green hydrogen in the Netherlands and across Europe. The programme addresses the system-wide
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programming, statistics, machine learning and big data approaches in the context of soil-vegetation-atmosphere interactions excellent writing and oral communication skills in English and strong ambition
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National Growth Fund-funded research project ‘Re-Ge-NL Opens external : Accelerator for the transition to a regenerative, profitable and socially supported agricultural sector’ in which a large consortium
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Postdoc in computational social choice for large-scale deliberation (1.0 FTE) (V25.0203) « Back to the overview Job description A 2-year postdoc position in computational social choice for digital
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uncovering companion biomarkers for precision treatment using cutting-edge bioinformatics and proteomics approaches. You will analyze bulk and clonal protein expression data from large melanoma cohorts