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strong research programme that encompasses research activities in the areas of urban informatics, spatial big data analytics, geographical information science, satellite positioning, ubiquitous positioning
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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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that combines functional, structural, spatial, and temporal information. This enriched representation will support both static validation and dynamic analysis, including the automatic synthesis of timed and
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, the successful applicant will analyze integral-field spectroscopy (IFS) data of starburst galaxies, with a primary focus on the spatially resolved star formation history and on the physical properties
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, selection, and clonal dynamics, using high-throughput sequencing and systems-level analysis. Work on the engineering and functional assessment of synthetic or ex vivo thymic environments to control immune
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: Analysis and interpretation of high-resolution single-cell RNA-seq and scATAC-seq data to elucidate cellular processes Processing and integration of spatial transcriptomics data to reveal molecular patterns
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. Your team You will collaborate with GRS colleagues who have expertise in methods and tools for spatiotemporal analysis of complex land systems (including agent-based modelling), spatial data
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across different spatial and temporal scales, from building-level energy demand to district-scale interactions and their integration with wider energy networks. PhD Position in Hierarchical Graph Neural
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and philosophers, including one other PhD student (statistics) and two postdocs (spatial forest ecology and philosophy/social science). The candidate is expected to contribute toward developing
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | 26 days ago
solving complex inverse problems that link measurements to their underlying causes. This PhD interdisciplinary programme focuses on Bayesian methods for estimating physical parameters from high-dimensional