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Field
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for collecting data on environmental and health parameters (air quality, noise, mobility). GIS Proficiency: Proficiency in Geographic Information Systems (GIS) to map and analyze spatial determinants of urban
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LiDAR and UAV photogrammetry) with physiological and spectral indicators of forest health. The research will be conducted at multiple spatial scales, from single trees to landscapes, and integrated
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candidate will contribute to projects involving participants with implanted intracranial electrodes and wearable non-invasive sensors, with a focus on memory consolidation, spatial navigation, and neural
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The successful candidate will be responsible for developing computational and systems biology approaches to analyze spatial omics data and single-cell omics data (e.g., scRNA-seq, scATAC-seq, single
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with R, statistical and spatial analysis Excellent communication and teamwork skills Excellent organizational skills Experience with field work in post-disturbance forest conditions (desired) Experience
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or closely related sciences*; Knowledge about spatial modeling, remote sensing, and geographic information systems; Knowledge and expertise in spatial modeling using satellite or airborne images and airborne
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advanced spatial statistics in R and QGIS is required. The ability to work both independently and collaboratively in a team environment is essential. Pay and Benefits Pay Range: $62,000 - $65,000; depending
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LiDAR and UAV photogrammetry) with physiological and spectral indicators of forest health. The research will be conducted at multiple spatial scales, from single trees to landscapes, and integrated
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for improving the environmental impacts of wood production over broad spatial scales. Required Skills and Qualifications: PhD in a forestry- or conservation-related discipline. Strong background in field survey
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of biotic heterogeneity in urban environments and the spatial/temporal dynamics of these drivers. This will involve working with pre-existing data collected by the lab, as well as collaborator data and