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related field. You bring a strong analytical background and experience with optimization models and quantitative analysis methods. Familiarity with urban energy systems, energy infrastructures, or spatial
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implement end-to-end data pipelines, develop AI models to extract structured intelligence from unstructured social media data, build spatial risk models, and translate these outputs into a secure, user-facing
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experiments, data analysis, and animal colony management. Beyond technical support, the successful candidate will be an essential part of daily lab functionality and will be mentored to design and lead
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is home to a consortium of postdoctoral fellows who provide modeling expertise for a wide range of projects as integral members of those research teams. Unit URL https://imci.uidaho.edu/ www.uidaho.edu
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are also required: at least one course in Programming at least one 2nd cycle course in one of: Stochastic processes, Machine learning, Time-series analysis, Spatial statistics, Spectral analysis
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analysis and statistical modeling. Experience working with large, complex, and multi-dimensional datasets. Experience with spatial analysis and geospatial data integration, including use of GIS tools (e.g
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-spatiale proposées, et l'idée de passage entre les soins en structure et au domicile. Le projet ARCADE vise à évaluer la faisabilité et l'efficacité d'un programme de rééducation cognitivo-motrice basé sur
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, Digital Soil Mapping, Remote sensing (COPERNICUS data ecosystem), spatial data modelling, spatial analysis, neural networks, large scale datasets management with GIS, cloud computing, Big Data tools. You
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, xenograft models, brain tumor biology, confocal imaging, immunofluorescence and/or FISH and/or computational analysis of scRNAseq/RNAseq/spatial transcriptomics Background in brain tumor biology Knowledge
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Foundation (FAPESP), and combines statistical analysis, spatial methods, and qualitative research. Georeferenced data from the Military Police and the Municipal Secretariat of Urban Security will be used