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: Experience with field- and laboratory work and data collection Strong skills in applied statistics, with documented experience Strong programming skills and experience in machine-learning Experience with GIS
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experiences and skills will be emphasized: Experience with handling large datasets and using R, GIS and bioinformatics tools. Experience with modelling methods, including analysis of ecological gradient
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background Documented proficiency in both oral and written English The following experiences and skills will be emphasized: Experience with handling large datasets and using R, GIS and bioinformatics tools
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basin. Teaching will typically be related to spatial ecology, GIS, ecosystem-based management or sustainability science. The applicants must present a description outlining the academic basis of the PhD
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modelling. Extensive experience from field work, especially in harsh and/or polar climates. Working with 3D geomodelling (e.g. Petrel, Move, Leapfrog) and GIS software (QGIS, ArcGIS). Previous experience in
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from field work, especially in harsh and/or polar climates. Working with 3D geomodelling (e.g. Petrel, Move, Leapfrog) and GIS software (QGIS, ArcGIS). Previous experience in integrating diverse type
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GIS software (QGIS, ArcGIS). Previous experience in integrating diverse type of data, such as processing and interpretation of digital outcrop models, structural data, sedimentological data, seismic
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, literature and selected material studies), 3) Existing palaeo-environmental data (geology, archaeobotany, shoreline displacement models), 4) GIS modelling (including topographic analysis, view-shed analysis
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, shoreline displacement models), 4) GIS modelling (including topographic analysis, view-shed analysis, least-cost-analysis, Tobler’s hiking function) and 5) Comparison of archaeological results with