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University, you will build models and methods to parse natural language questions into geo-analytical workflows, combining NLP and semantic representations to improve how complex spatial questions can be
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PhD: Semantic Modelling of Geodata Sources and Geo-analytical Workflows Faculty: Faculty of Geosciences Department: Department of Human Geography and Spatial Planning Hours per week: 36 to 40
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processing and machine learning methods, and big data analytics solutions to extract highly accurate large-scale geo-information from big Earth observation data. Our team aims at tackling societal grand
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Boreal forest recovery after clear-cut: We are looking for a highly motivated PhD student to collect data on and model hydro(geo)logy and greenhouse gas exchanges of boreal forests after
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serve as a co-investigator in research on prebiotic (geo) chemistry and the origins of life. This position is part of an interdisciplinary environment that integrates geosciences, chemistry, and physics
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data and models is an advantage Experience in geo- or paleomagnetism is an asset What we offer: Ambitious and varied tasks in a dynamic and international research environment State-of-the-art equipment
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include application of process-based models (e.g., CANDY, DayCent, LDNDC, Daisy) to model within-field N-fluxes (e.g., N2O-losses, NO3-leaching, N-mineralization) support model parametrization, estimate N
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budget. Tasks include application of process-based models (e.g., CANDY, DayCent, LDNDC, Daisy) to model within-field N-fluxes (e.g., N2O-losses, NO3-leaching, N-mineralization) support model
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biogeochemical cycling, individual PhD projects can involve aspects of (geo-)microbiology, soil science, atmospheric measurement techniques, atmospheric transport models, terrestrial and atmospheric remote sensing
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Description As part of a multi-disciplinary, integrated research team, the candidate will participate directly in efforts to relocate seismicity and to provide subsurface velocity models and geo