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projects in computer vision research, with a particular emphasis on Spatial Intelligence, 3D Computer Vision, and 3D Generative AI. You should hold a relevant PhD/DPhil (or near completion*) in Computer
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. These data will be complemented by data from a bespoke survey, designed and analysed by other members of the team. The results from the digital ethnographies will feed into spatial micro-simulation and agent
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conservation of marine and coastal ecosystems. The successful candidate will also require strong technical skills in terms of statistical and spatial analyses, and the ability to coordinate and manage large
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Postdoctoral Scholar to conduct research for an NIH-NSF funded project on human health, movement, and infectious diseases. Successful applicants will have experience in: either spatial analysis using GIS
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manipulation, viral gene therapy, pharmacological studies, gene editing, and physiological measurements of cardiac electrical and mechanical function at a variety of spatial scales from a single cell to whole
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Proficiency: Proficiency in Geographic Information Systems (GIS) to map and analyze spatial determinants of urban health. Predictive Modeling Skills: Ability to develop predictive models and simulation tools
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devices into complex digital systems. Advanced expertise in machine learning and artificial intelligence for predictive and prescriptive urban data analysis. Experience in visualizing and analyzing spatial
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assessment in urban environments. Proficiency in hydrological modeling software (SWMM, HEC-RAS, or equivalent). Experience with GIS tools (ArcGIS, QGIS) for spatial analysis and mapping of water flows and risk
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] that process information in temporal rather than spatial modes to reduce their footprint. The project involves a collaboration between DTU Electro (Senior Researcher Mikkel Heuck) and Harvard University (Dr
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work with researchers and students involved in spatial hydrology. Publish scientific papers in peer-reviewed journals and deliver presentations and progress reports. Contribute to the supervision