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processing, and data visualization will be important. Spatial data models are natural starting points, and research on Geographical Information Systems (GIS) is expected to be central. Empirically
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integration, data storing and processing, and data visualization will be important. Spatial data models are natural starting points, and research on Geographical Information Systems (GIS) is expected to be
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(or a strong interest) in developing and leading large research grant proposals. Additionally, it would be an advantage to also have: Experience with GIS software, and/or Experience working with
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clear advantage. Familiarity with spatial data analysis in R (GIS) is also an advantage. Applicants must be able to work independently and in a structured manner and demonstrate good collaborative skills
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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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, geography, spatial economics, computer science or related fields. You must have a professionally relevant background in conducting research or working with research projects. Advanced knowledge of GIS
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breeding season is a clear advantage. A documented interest for fieldwork involving wild birds in Scandinavian weather is a clear advantage. Familiarity with spatial data analysis in R (GIS) is also an
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advantage. Familiarity with spatial data analysis in R (GIS) is also an advantage. Applicants must be able to work independently and in a structured manner and demonstrate good collaborative skills
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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