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modeling; and GIS/remote sensing. Proficiency in R and/or Python and experience working in a high-performance computing environment. Excellent written and verbal communication skills. Strong interpersonal
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laboratory data. strong skills in GIS, spatial statistics, digital soil mapping, geostatistics or related quantitative methods. proficiency in reproducible data analysis using R, Python or equivalent software
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Instituto de Geografia e Ordenamento do Território da Universidade de Lisboa | Portugal | 22 days ago
. The successful candidate will support research activities related to Geographic Information Systems (GIS), spatial statistics, accessibility modelling, territorial typologies, dashboard development, and scientific
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Streamlit or Dash) that integrate GIS mapping to visualize infrastructure, climate, and crop distribution. Scenario & Data Modelling: Translate techno-economic models (CAPEX/OPEX) into interactive Python
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review, and with geochronological methods used to date past earthquakes Proficiency with relevant mapping, drafting, GIS, and structure-from-motion software Good written and oral communication skills
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(e.g., laser scanning, optical satellite imagery, radar, UAV, or aerial imaging). Strong programming and data analysis skills (e.g., Python and/or R), as well as proficiency in GIS software and
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environment data for Singapore from government agencies and open sources, using GIS software (i.e. QGIS), R, and Python. Undertake 2D and 3D geospatial modelling and analysis. Apply spatial and statistical
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. Demonstrated competence of programming languages, such as Matlab, R, or Python, within a GIS environment Ability to publish and communicate effectively to both technical and non-technical audiences Ability
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listed in the project description above (ideally SAR for cryosphere applications) Strong programming skills (preferably Python or MATLAB) Strong background in statistics Fulfillment of the requirements
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physical activity promotion. Learn how to apply quantitative and qualitative analytic methods, including opportunities to use GIS, statistical software (R or Python), and emerging analytic approaches