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aims to develop a tool for real-time quantification of crop evapotranspiration at the field scale using a combination of in-situ measurements, satellite data, and modeling techniques. In-situ
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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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reality and mixed reality; data modelling and databases, in particular the spacecraft reference database; semantic modelling in support of digital continuity and semantic interoperability; digital twin
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English, both spoken and written. Additional experience that would be considered a plus: - some experience in programming and the use of computer algebra in algebraic geometry; - experience with
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assessment. You will be provided with access to various engineering and computation toolsets along with the high-performance computer. A good background in numerical methods and computational platforms is
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spoken and written. Additional experience that would be considered a plus: some experience in programming and the use of computer algebra in algebraic geometry; experience with noncommutative algebraic
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of our teaching and research. We therefore invite applicants from underrepresented groups in particular to apply. For more information, see also our diversity policy webpage: https://www.rug.nl/about-ug
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. actively contributing to the preparation of other strategy/decision papers and reports, as well as information notes or other reporting media. preparing training materials and providing training within
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academic debate and contributes to the quality of our teaching and research. We therefore invite applicants from underrepresented groups in particular to apply. For more information, see also our diversity
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on your interest and qualifications) contribute to (mobile) greenhouse gas monitoring strategies, their operations at (sub-) ecosystem to regional scales and to related data processing, aggregation and