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research papers; present research-in-progress at e.g. workshops/conferences; contribute to spatial analysis and GIS-related courses of the department; follow a 30EC training programme to prepare for your
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of coding (R and/or Python), enthusiasm for quantitative analysis Desirable: GIS/remote sensing, bioacoustics, machine learning, or statistical ecology. Field experience is useful but not required. Impact and
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, geospatial analyses and/or statistical modelling, satellite data retrieval; preferably experience with Pascal programming language and R or Python and geographic information systems (GIS); a proactive attitude
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or habitats knowledge of data analysis, statistical modelling or remote sensing experience with GIS, programming (R/Python) or handling large datasets demonstrated interest in method development or biodiversity
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analysis, statistical modelling or remote sensing experience with GIS, programming (R/Python) or handling large datasets demonstrated interest in method development or biodiversity research Great emphasis
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if interested. More information on the internship program is available here: https://kgs.ku.edu/geohydrology-internship-program POSITION: KGS Geohydrology Internship Program STARTING DATE: Week of May 26, 2026
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methods, or forest ecology - Advanced Skills in R/Python, GIS, bioinformatics, and molecular lab work - Ability to work independently and in multidisciplinary teams - Strong English communication skills
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on spatial reasoning, semantic technologies and AI for geosciences. Where to apply Website https://www.academictransfer.com/en/jobs/356999/phd-semantic-modelling-of-geoda… Requirements Specific Requirements A
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LCA software (SimaPro, OpenLCA, Brightway). Skills in R or Python for data processing and analysis. Experience with soil or biodiversity monitoring methods. Experience using GIS (QGIS, ArcGIS
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management Nordic forestry Remote sensing data: ALS, TLS, satellite (e.g. sentinel2), aerial images Statistical modelling and analysis GIS e.g. ArcGis, Qgis, R Programming, e.g. R, Python, C etc. Field work