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, as is knowledge of GIS or quantitative data analysis. The successful applicant is expected to work independently as well as collaboratively within an international research team. Strong analytical
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University of New Hampshire – Main Campus | New Boston, New Hampshire | United States | about 4 hours ago
communication skills Ability to work in a team setting and be self-motivated Other Requirements: Established publication record in peer reviewed journals Preferred Qualifications: Experience with GIS, UAV data and
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undergraduate or graduate researchers. · Experience writing research grant applications. · Experience with software such as R, Python, Matlab, and GIS tools · Experience facilitating workshops
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University of New Hampshire – Main Campus | New Boston, New Hampshire | United States | about 4 hours ago
for publication, including GIS. Additional Experience: Strong written and verbal communication skills. Proven ability to meet deadlines. Ability to effectively survey and read relevant scientific literature, and
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on the following subfields: (a) Geographic information science: cartography, GIS, data analysis and visualization, spatial analysis and modeling; (b) Human geography: political-ethnic, cultural, human-environment
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graduate education in the Department of Geography focuses on the following subfields: (a) Geographic information science: cartography, GIS, data analysis and visualization, spatial analysis and modeling; (b
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initiative proven through international publications in peer-reviewed media Didactic skills / experience in e-learning IT skills (e.g. Office, databases, GIS), excellent archaeological excavation and technical
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programming and strong quantitative skills. Desirable Demonstrated knowledge of advanced biogeographic, comparative, and phylogenetic methods, quantitative methods in biodiversity studies, GIS in R, and spatial
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, Hydrology, Environmental Science, or a related field. Experience in machine learning or AI applications in hydro-climate studies. Strong background with GIS tools and spatial analysis techniques. Demonstrated
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structuring of river systems. Familiarity with software and tools for simulating river network dynamics, such as R, Julia, Python, or GIS-based hydrological modeling platforms. Ability to integrate physical