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, and the production of regional climate datasets at high spatial and temporal resolution. The activities will also include the development of modelling tools and decision-support systems for climate
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computational field, such as complex systems, data science, urban systems, spatial modelling, engineering, geography, computational social science or a related discipline. You demonstrate the ability and ambition
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cutting-edge approaches, such as gene editing technologies, in vivo or in vitro model systems, and integration of omics (e.g. spatial transcriptomics or proteomics) and imaging data. Computational and
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, or others. Experience utilizing machine learning techniques to develop explanatory or predictive models for spatial datasets. Equipment Utilized ESRI ArcGIS software platform, Microsoft Office (Word
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are emerging as potential levers to mitigate the effects of warming. We welcome applications that propose to carry out lab, field or modeling research to understand warming effects on methane emissions
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, Spatial data analysis or GIS Whole-genome sequencing, phylogenetics, or phylodynamics Data management and reproducible analytical workflows Quantitative modeling and statistical inference. Applicants
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will contribute to a spatialized, dynamic life cycle assessment of ruminant production systems in the Northeast U.S. using integrated assessment models. The candidate will also contribute
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(see references below), we want to open a new route to synthetic cells and to their spatial organization: high-resolution 3D printing to enable placement with µm precision into controlled landscapes and
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to millennia. A central objective is to improve the representation of marine carbon, nutrient cycling and microbial processes in Earth System Models while increasing spatial model resolution to capture key
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spatial omics, genetically engineered mouse models and clinically annotated human cohorts to understand the molecular mechanisms driving rare kidney cancers. The successful candidate will benefit from state