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and Stata. Working with large datasets, including merging files into the data archive. Creating clear data visualizations to communicate results (including GIS maps). Assisting with the preparation
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escrita en español e inglés - Experience in analysing traffic accident data and road safety - Advanced knowledge of spatial analysis and Geographic Information Systems (GIS). - Proficiency in statistical
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/PhD) or related field. - Simulation & data: TRNSYS (or similar), time-series processing; Python (pandas/numpy). - Experience with GIS and/or climate/solar datasets (e.g., METEONORM, PVGIS
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(quantitative, qualitative, modelling, GIS, etc.). Produce and share research outputs such as: articles and preprints, demonstrators or prototypes, documented datasets and, where possible, open data, a scientific
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objectives (e.g. geography, biology, epidemiology and public health). The person recruited will have competence in statistical analysis and GIS, experience or at least interest in carrying out field work and
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monitoring. Responsibilities Drive forward the department’s analytical and statistical expertise in remote sensing, LiDAR, AI tools, GIS, and spatial modeling. Take a leading role in developing digital tools
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monitoring. Responsibilities Drive forward the department’s analytical and statistical expertise in remote sensing, LiDAR, AI tools, GIS, and spatial modeling. Take a leading role in developing digital tools
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or similar areas, and fully comply with the following requirements: The doctoral degree must have been obtained at least 1 year ago; Proven experience in GIS environment analysis (QGIS, ArcGIS, R), statistical
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Additional Information Eligibility criteria Technical skills: proficiency at ecological modelling, use of the Unix/Linux environment, proficiency at oceanographic data repositories and GIS tools, good
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Professor that will be capable of contributing to multiple ongoing research projects in the lab. Potential projects include, but are not limited to, oceanographic characterization of deep-water habitats, GIS