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developing a collection of spatially distributed models for these objectives within an encoder-decoder framework to reduce the dimensionality, enabling the use of multi-objective optimisation to generate a
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PhD Scholarship This project will use existing modelling and planning tools to evaluate and refine global carbon and biodiversity market design strategies. The student will gain expertise in
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research methods applied to urban contexts.• Experience with spatial modelling software (Metashape), geographic information systems (ArcGIS Pro), creative tools(Photoshop), and quantitative (SPSS) and
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framework to model complex catalytic materials with near ab initio accuracy while enabling simulations at significantly larger spatial and temporal scales than conventional electronic structure methods
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for the Modeling of Biological and Sociotechnical Systems (MOBS Lab) within the Network Science Institute at Northeastern University. MOBS Lab focuses on research projects aimed at developing innovative mathematical
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develop open-source, surrogate models of land-atmosphere exchange, at various spatial resolutions and using various methodologies, to contribute to a better understanding of the carbon and climate impacts
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that has revealed the existence of scaling laws in the spatial organization of cities, particularly concerning the succession of land uses from the city center (highly urban land use) to the periphery
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immunologists and chemists and integrates state-of-the-art omics approaches, including single-cell RNA-seq and spatial transcriptomics, performed in partnership with the GenoEast platform. The collaborative
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Design, develop, and implement advanced algorithms, models, and software tools for spatial data analysis, machine learning, and AI-driven geospatial applications Lead and collaborate on interdisciplinary
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and immune trafficking models. High-Resolution Imaging: Proficiency in spatially-resolved multiplexed imaging and confocal whole-mount tissue analysis. scRNA-seq: Experience designing 10x Genomics