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some academic research experience post-Master level. Demonstrable affinity with archival sources. Strong skills in GIS-based research, additional experience with computer vision and machine learning is a
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PhD Biodiversity responses to regenerative livestock practices in the Espinal woodlands of Argentina
of remote sensing, Geographic Information System (GIS), and the R statistical program is appreciated, as well as background or interest in participatory and social methods. The successful candidate should
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strong analytical skills and GIS expertise (e.g., spatial analysis, DEM interpretation). The candidate should also have an interest in - and experience with - Quaternary geology, geomorphology
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competence in urban planning / urban design Excellent writing ability and good interpersonal skills GIS &/or architectural visualisation skills will be looked upon favourably, but not essential Successful
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Agronomic Engineering or a related field; -Specific requirements: Knowledge in agronomy, water resources, remote sensing, GIS tools; strong organizational skills; good proficiency in spoken and written
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PhD Biodiversity responses to regenerative livestock practices in the Espinal woodlands of Argentina
related disciplines such as Ecology, Environmental or Agricultural sciences. Basic knowledge of remote sensing, Geographic Information System (GIS), and the R statistical program is appreciated, as
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analysis and GIS Demonstrated, strong analytical and research skills Experience handling, analysing and presenting large telemetry datasets Interest in translating science into action (marine spatial
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or modeling. If you've dabbled in GIS, that's a bonus! Willingness to Learn: You're excited to deepen your knowledge in areas such as forest economics, forest management, economic theory, spatial analysis
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programming (e.g., R or Python) is desirable. · Experience with GIS or remote sensing techniques is advantageous. · Excellent written and verbal communication skills in English. A CV (max 3 pages
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). • Experience handling large datasets from empirical studies, surveys and GIS desirable. • Interest and experience conducting research in livestock systems, agricultural technologies. • Interest in