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qualifications in probilistic risk modelling, applied statistics and familiar with quantitative risk modelling measures strong data analysis skills and proficiency in R and Python; experience with other programing
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predictive modelling Public policy evaluation Management and analysis of survey data Software proficiency Statistical and econometric packages such as Stata, R, or Python GIS software (QGIS, ArcGIS
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; - No employment contract, or proof of full unpaid leave, in accordance with FAPESP regulations . Desired Skills: - Proficiency in R, Python, and JavaScript (Google Earth Engine); - Geoprocessing and GIS
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Bioinformatics expertise of Dr. Raimondi on the development of GI NN methods and their application to relevant biological problems with the expertise of Dr. Bry and Dr. Trottier on the statistical inference
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. Excellent proficiency in spatial and statistical programming (e.g., R, Python, or Google Earth Engine). Proficiency in, and commitment to, version control (e.g., Git), reproducible research practices, and
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record of publications in relevant fields. Have proficiency in data processing and statistical analysis, with experience in programming languages/software such as MATLAB, Python, R, Stata, as well as GIS
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experience in remote sensing and GIS, strong programming skills (Python, R or similar), and an international publication record. Experience with machine learning and cloud computing will be considered an asset
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/C++, FORTRAN and/or Python. Experience working with geo-spatial information, remote sensing data, and GIS software. Experience in deep learning and computer vision. Experience in developing software
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stronginterest and experience with GIS data and tools for urban mobility with someprogrammingskills of Python/R, JavaScript, database management environments, Geographical AI and machine learning workflows
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Nature Careers | Cape Winelands District Municipality, Western Cape | South Africa | about 2 months ago
recognized Ph.D. completed within the last 5 years in remote sensing, environmental monitoring, forest science, or another applicable field, with demonstrable experience in GIS and proficiency in Python and