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axes: AI-driven territorial diagnostics and foresight, integrating multi-source satellite data with machine learning and spatial modeling Climate–water–energy–agriculture interactions, with applications
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 17 days ago
: Advanced degree (PhD) in statistics or bioinformatics relevant field. Experience with analysis in R. Essential Skills: Degree in statistics or bioinformatics relevant field. Three or more years of analysis
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communities • Multivariate statistical analysis of community and environmental datasets • Spatial analysis and georeferencing of ecological data using GIS • Development and implementation of species
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on complex problems involving the development of new theories and methodologies. The research will be largely focused on the development of predictive computational tools for the analysis of the spatial spread
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Candidate Profile Training and Skills required (Recent) PhD in bioinformatics, statistics, or computer science with knowledge and interest in biology Track record of creativity in developing analytic
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Science in Urban Informatics & Smart Cities and Doctor of Philosophy. LSGI has a very strong research programme that encompasses research activities in the areas of urban informatics, spatial big data
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interdisciplinary research teams and internal and external partners. Required qualifications Applicants must have: A PhD in ecology, marine biology, statistics or a related discipline. Strong expertise in statistical
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11 Apr 2026 Job Information Organisation/Company Lunds universitet Department Lunds universitet Research Field Mathematics » Statistics Researcher Profile Recognised Researcher (R2) Application
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interdisciplinary research teams and internal and external partners. Required qualifications Applicants must have: A PhD in ecology, marine biology, statistics or a related discipline. Strong expertise in statistical
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Multivariate statistical analysis of community and environmental datasets Spatial analysis and georeferencing of ecological data using GIS Development and implementation of species distribution models