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programming and data analysis tools (e.g., SQL, Python, R, GIS platforms); experience with the management and analysis of human subject data (e.g., from questionnaires, interviews, behavioural experiments, eye
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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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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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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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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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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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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
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. The applicant must have experience in Dynamic WebGIS site development. Geospatial (remote sensing, GIS, & GPS) data acquisition and processing through advanced Data/Image Mining Data Fusion Approach development
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changes to hydrometeorological forcing. Geomorphology, 414, 108383, https://doi.org/10.1016/j.geomorph.2022.108383 Eelsalu, M., Viigand, K., Soomere, T., Parnell, K., 2024a. Systematic analysis
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trends. Experience with statistical computing programs including R, python, stata, or similar program. Experience with GIS and VamaNet or similar program. Pay Band {lPayScaleID} Overtime Status Exempt: Not