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science, GIS, computer science or other relevant disciplines • Good background knowledge and overall interest in design technology • Proficient in statistical and programming skills, like Python
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of GIS software as well as word processing and spreadsheet programs Knowledge of programming languages such as R or Python desirable Experience in organizing workshops is desirable Very good written and
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fields. Additional optional skills and qualifications: Knowledge of coastal geology. Knowledge and experience in programming with Python and in GIS. Availability and motivation to participate in field
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programming and analytical skills (e.g., Python, R, GIS, modeling frameworks). Experience working with EO data, disease surveillance data, or socio-environmental modeling. Demonstrated interest in
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qualification (doctorate) Requirements: Completed scientific university degree in geography, (geo)informatics, landscape ecology or comparable disciplines Profound knowledge of GIS software, programming languages
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sediment and particle transport and fluid dynamics Publications in the relevant field Preferred selection criteria Experience with programming and data analysis using Matlab, Python, or similar tools
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include strong skills in GIS, large dataset handling, Python programming, and a record of scientific publications in the field. Excellent command of English, both spoken and written, is expected. Merits
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Institute of Systems and Robotics-Faculty of Sciences and Technology of the University of Coimbra | Portugal | about 1 month ago
-acquired above-the-canopy mapping within the broader ForestSphere Digital Twin architecture (e.g., integration with understory maps at ground level and sensor-derived mapping data with GIS systems
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(GIS); - Programming skills in Python and MATLAB. Additional optional skills and qualifications: - Good command of English. Contracting requirements: Presentation of the academic qualifications and/or
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processing environmental exposure and health administration data via Application Programming Interfaces (APIs) proficiency using statistical programming software such as R, SAS, STATA and Python; and GIS