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Instituto de Geografia e Ordenamento do Território da Universidade de Lisboa | Portugal | 4 days ago
of geospatial information through Web Feature Services (WFS); Excellent command of Portuguese and English, both written and spoken. Specific Requirements Applicants must hold a Master's degree in Geography
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to Elders past and present. · Drive innovation in digital forestry and geospatial analytics · Work with industry to translate research into operational outcomes · Relocation support may be available
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to sedimentological and biogeochemical investigations contribute to modelling sedimentary copper systems and Earth surface processes analyse and interpret large-scale geospatial and geochemical datasets publish high
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Proficiency in Python for geospatial data handling, model workflows, and scientific computing Strong communication skills and enthusiasm for interagency scientific research Application Requirements A complete
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remotely sensed information with field observations and environmental datasets; quantify spatial and temporal changes in willow cover, density and landscape configuration using advanced geospatial techniques
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the guidance of a mentor, you will learn about (1) geospatial processing and ML/AI methods and (2) how to contribute to SCINet and the ARS AI Center of Excellence community by developing and publishing workflows
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new international Master of Science (Technology) degree programme, particularly in the fields of remote sensing and geospatial computing, while also advancing research on digital waters. The position is
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in geospatial data analysis is an advantage. Applicants must be able to work independently and in a structured manner and demonstrate good collaborative skills. Applicants must have good written and
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events and in machine learning for the earth system is required Strong and demonstrated programming skills are required Prior experience with geospatial data analysis in Python, working on scientific HPC
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. Demonstrated proficiency with scientific programming (e.g. Python) is an advantage. Demonstrated proficiency in geospatial data analysis is an advantage. Applicants must be able to work independently and in a