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Field
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spatial biology, single-cell RNAseq Multiplex, etc and animal (mice) models such as humanized mice, PDX models and other models simulating patients. Responsibilities Designs and conducts research on cancer
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microenvironment. The project will employ genetically engineered mouse and human glioma models, along with advanced imaging techniques, single-cell and spatial transcriptomics, and molecular biology approaches
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of metabolic states in retinal ganglion cells; spatial transcriptomic and correlated metabolic analysis of retinal ganglion cells; treatment of retinal ganglion cells in models of degeneration; data collection
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Proficiency: Proficiency in Geographic Information Systems (GIS) to map and analyze spatial determinants of urban health. Predictive Modeling Skills: Ability to develop predictive models and simulation tools
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, developmental biology, genetics, biomedicine, or another appropriate field. Previous experience in confocal imaging and image analysis, scRNA-seq data analysis, or genetically engineered mouse models is
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variety of) behavioural and/or cognitive traits (e.g. birdsong, exploration behaviour, personality, (social) learning, social and spatial cognition etc…) in free-living birds. to quantify anthropogenic
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computer programming tools such as Matlab and/or Python. Knowledge of statistics and mathematical modeling. Experience in large spatial data processing, analysis, and interpretation. Experience in running
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, organizational, and analytical skills PREFERRED QUALIFICATIONS: Molecular/synthetic biology, single-cell sequencing, or in vivo cancer models Evolving or static barcode-based lineage tracing Computational analysis
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PostDoc in "Sustaining the keystone: Rethinking Antarctic krill fishery management under climate ...
occurred during the October 2024 CCAMLR meeting: the expiration of Conservation Measure (CM) 51-07, which previously mandated that the maximum annual allowable catch of 620.000 t be spatially distributed
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hydro-climate studies. Strong background with GIS tools and spatial analysis techniques. Demonstrated expertise in climate variability assessment and the use of climate models. Experience with