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motivated individual with capacity to work independently. Good time management and planning; Good publication track record; Some knowledge of Building Energy Modelling, GIS and programming language (Python, R
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. Additional Skills (Preferred): Experience with environmental data analysis (R, Python, multivariate statistics). Experience in GIS and ecological mapping. Strong scientific writing skills and command
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synthesis, (b) numerical and analytical modeling environments (e.g. Python), (c) geoprocessing and GIS analytics, and (d) data-driven model development. Demonstrated ability to meet deadlines and effectively
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soil and crop scientists, GIS specialists, remote sensing experts, and computer programmers. They will be responsible for: Conducting fieldwork using UAVs (drones) to capture high-resolution imagery and
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classification. Strong background in experimental design, statistical sampling and analysis in field settings. Skilled in GNSS‑based geolocation, GIS software (e.g. QGIS, ArcGIS) and programming (Python, R
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Dalhousie University | Halifax Mid Harbour Nova Scotia Provincial Government, Nova Scotia | Canada | 21 days ago
support tool for non-GIS users, e.g., Enterprise GIS databases, ETL workflows for data sharing, ArcGIS Dashboards; ▪ Demonstration of intermediate knowledge of python scripting and experience working with
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”. Qualifications Applicants should: (a) have a PhD degree in Remote Sensing, Geomatics, GIS, Computer Science, Photogrammetry or a related field, and must have no more than five years of post-qualification
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methods to economic and environmental problems; Knowledge of STATA, R, Python and/or other relevant programming skills for undertaking applied analysis (e.g. machine learning) and handling large
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and maintain Python and R codebase for transit routing and GIS operation automation. · Generate and write grant proposals with Dr. Liu on various topics. · Work with undergraduate and graduate students
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computational modeling, geometric morphometrics, multivariate and Bayesian statistics, spatiotemporal and spatial modeling (including GIS), causal inference, machine learning, AI, and statistical software