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. Our mission is to move beyond descriptive biology and develop predictive, mechanistic models that connect molecular regulation to cellular and systems-level phenotypes. The Laboratory of Computational
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. The project will construct the first-ever Spatial Integrated Assessment Model of the global water cycle. Combined with global spatial data on economic activity, water usage, and atmospheric evaporation
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statistical models. Within the Polarity, Division and Morphogenesis team, the candidate will work closely with biologists and physicists to develop approaches integrating spatial transcriptomics, cell dynamics
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materials systems at the molecular level with machine learning. The PhD Student will work with tumour sections to develop multiple instance learning and weak supervision / spatial transcriptomics models
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metadata documentation Manage geospatial datasets and version control systems (e.g. ArcGIS Online, Git, or QGIS project files). Spatial Analysis and Modelling Use GIS software (e.g. ArcGIS, QGIS) and/or
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technologies, spatial omics data, immunology and cancer systems biology. Experience with genomic engineering methods, stem cell culture, flow cytometry, and murine models is preferred. Ability to work
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. Our mission is to move beyond descriptive biology and develop predictive, mechanistic models that connect molecular regulation to cellular and systems-level phenotypes. The Laboratory of Computational
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nécessaire pour suivre les bilans des gaz à effet de serre, la production de biomasse et les rendements agricoles. À ce jour, la plupart des méthodes permettant d'estimer spatialement la GPP s'appuient soit
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mortality will occur. A second coarser-resolution model will be developed over larger spatial scales using different data sets. The postdoctoral fellow will be responsible for analyzing the data sets
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focus on the conceptualisation and prototyping of spatial data infrastructures and registries for space environments and objects. The role involves research into spatial data models for representing