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6 Sep 2026 Job Information Organisation/Company CNRS Department Laboratoire "Atmosphères et Observations Spatiales" Research Field Mathematics History » History of science Researcher Profile First
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Research Assistant to support an AcRF Tier 1 project on sparse boosting for high-dimensional spatial autoregressive models. The successful candidate will contribute to methodological development, simulations
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team, this role provides essential research and visual support across both the spatial analysis and qualitative components of the project. Qualifications • Bachelor's degree in Landscape Architecture
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, which may include working extended hours and weekends. Required qualifications: • Bachelor’s degree in forestry, natural resources, spatial sciences, emergency management, or related
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, Computer or Data Science, Remote Sensing, or a related field. Proficiency in Python and experience with geospatial data processing, spatial analysis, scientific programming, data visualization
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risk factor analysis. Ability to design and execute spatial statistical models to identify geographic patterns of disease risk at the community level. Ability to build and validate predictive models
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models that includes breeding colony management and genotyping. Performs advanced 3D and spatial imaging (confocal, LSFM, Xenium spatial transcriptomics) and associated computational image analysis
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on departmental needs and the candidate’s background and interests, these courses may cover areas such as GIS foundations, cartography, remote sensing, spatial analysis and modeling, spatial databases, machine
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on single-cell and spatial genomics data, from sequencing and imaging, and apply them to human developmental and disease biology. Possible research directions include: ● Generative models of cell–cell
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University of Toronto | Downtown Toronto University of Toronto Harbord, Ontario | Canada | about 3 hours ago
curriculum. Minimum Qualifications: Ph.D. (Geography, Urban Planning, Data Science or related field). Demonstrated expertise in urban data analytics, Geographic Information Systems (GIS), spatial analysis