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to § 2 WissZeitVG) on the research topic Remote sensing of aerosols and their properties in the Arctic using satellite data Both positions are embedded in the third phase of the very successful
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. The project will allow other tech companies to link their systems up, such as disease prediction models, remote crop health monitoring and methane monitoring to start to bring real productivity gains to UK
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loss data. Computing skills including experience in advanced statistic programming languages (R and/or Python), remote sensing and GIS software (Google Earth Engine, ArcGIS and/or QGIS). Demonstrated
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cycling, and water use efficiency. -Develop decision support tools and yield forecasting platforms using crop models, remote sensing data, and advanced data analytics. -Collaborate with farmers and
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letter; e) Knowledge of quantitative (including modelling) and qualitative research methodologies, remote sensing and GIS techniques and long-term ecological data analysis - information provided in the CV
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space-time data, e.g. from remote sensing of the Earth. Traditional prediction methods are not suitable for such data, mainly due to high computational complexity as well as other limitations [1]. Recent
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PhD in remote sensing, geophysics, computer vision, machine-learning, geography or similar Experience in handling netcdf and shapefiles in Python (xarray, geopandas) Experience in image segmentation and
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. Preferred requirements: Preference will be given to candidates with experience in spatial ecology, biogeography, geographical information systems, remote sensing, ecological niche modelling, R, and Google
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. The department “Lidar” develops ground-based, airborne and spaceborne lidar systems. It applies them for active remote sensing of key meteorological parameters and atmospheric trace gases enabling research in
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of Sensing, Imaging and Modelling (DREAM) at the University of Oulu. DREAM will educate in total 100 doctors located at 7 Finnish universities in a diverse and multidisciplinary setting, encompassing applied