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hazards and assessing their risk for the society. At the same time, they are fully qualified users of remote sensing, GIS and statistictical software techniques that can be applied to geoscience and
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preferred) Experience with processing and analysing remotely sensed data Experience with GIS and spatial data analytical techniques Experience with carrying out fieldwork in related fields (e.g. Geography
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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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, epidemiological, and environmental data Taking part in developing and validating predictive cancer‑risk models Contributing to spatial analysis and data integration in geographic information systems (GIS
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systems is a merit, especially hydromechanics. It is an advantage to have experience in data management, GIS, statistics and programming. The applicant must be able to work both independently and in a group
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developed: • High-resolution documentation of selected sites: photography, photogrammetry, DStretch® and GIS integration, digital tracing; • Non-invasive sampling of pigments and physical-chemical
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for GIS, cartographic maps, geodata infrastructures and geo-analytical workflows; some experience with AI and machine learning methods to label texts (NLP) or data sources; strong programming skills (e.g
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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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with process based erosion models, field measurements and atmospheric boundary layer processes detailed knowledge of GIS, Google Earth Engine, and programming in these systems high degree of initiative