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data (nationwide LiDAR coverage at 50 cm resolution). The candidate will perform quantitative morphometric analyses of landscapes and river networks near suspected active faults using GIS tools, Python
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., examples of program codes (Python, R, SQL, GIS scripts, etc.), description or documentation of technical solutions to research problems in which the applicant participated (spatial data processing
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Health, Data Science, Remote Sensing, Geomatics or a closely related discipline•Strong analytical and programming skills (e.g. Python or similar)•Experience in at least two of the following areas
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | 3 months ago
or territorial studies. Preference will be given to candidates with aptitude for working in disaster risk management environments supported with GIS and Machine Learning, basic programming skills (e.g., Python, R
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, generating evidence to support long-term climate adaptation and investment planning. Students will build a comprehensive set of high-value technical and professional skills, including: • Geospatial and GIS
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(preferably in R, Python, GIS) • Competences in quantitative research methods - ideally knowledge of several of the following aspects of quantitative data analysis: analysis of large/longitudinal datasets
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-authored peer reviewed papers) • Well-developed statistical software skills (preferably in R, Python, GIS) • Competences in quantitative research methods – ideally knowledge of several of the following
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experience in academic writing for publication (e.g. first or co-authored peer reviewed papers) Well-developed statistical software skills (preferably in R, Python, GIS) Competences in quantitative research
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) • Preferably demonstrable experience in academic writing for publication (e.g. first or co-authored peer reviewed papers) • Well-developed statistical software skills (preferably in R, Python, GIS
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urban design with microclimate simulations and measurements, GIS and Digital Twin technologies, and machine learning. The work will be part of a Horizon pilot project aimed at realizing a scenario-based