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Field
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Lab ). Integrative analysis of single-cell multi-omics and spatial imaging data in cancer, immunology, organoids, etc., in the context of the Human Cell Atlas (single-cell analytics) and/or the ELLIS
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able to analyse complicated data. Good statistical knowledge and experience with geo-spatial analysis techniques is a benefit. Prior knowledge on wetland ecosystem functioning, and particularly on carbon
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for flood risk estimation, and prototyping flood monitoring and forecasting procedures at very high spatial resolution. The candidate will collaborate closely with the Remote Sensing and Hydrology lab and the
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, analysis, architecting, and design is desirable. Smart, Connected, and Healthy Communities: Smart Integrative Energy Systems The Ezra Systems Post-Doctoral Associate on the track of Smart Integrative Energy
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spatial function) and alpha-synuclein (a protein that causes Parkinson’s disease and Dementia with Lewy Bodies) affect brain circuits. The postdoc’s work will encompass studies that are actively collecting
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computational modeling techniques to study planning in rodents engaged in dynamic spatial foraging tasks. The successful candidate will develop computational models of reinforcement learning in the brain and
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cytometry Perform genomic data analyses from next generation sequencing data (eg. RNAseq, scRNAseq, spatial ‘omics profiling)—prior experience with genomic data analysis is helpful but not required Stay
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computing clusters and analysis of transcriptomics and genomics datasets. Desirable Requirements Experience in single-cell and spatial OMICS data analysis. Development of ShinyApps and
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methods for single-cell data analysis (tools developed by the team : https://github.com/cantinilab ). Single-cell high-throughput sequencing, extracting huge amounts molecular data from a cell, is creating
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research, including such topics as microclimate, watershed management and modeling, sediment analysis, soil formation, water scarcity and security, geomorphology, land cover change, application of remote