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Texas and the Gulf Coast region. Experience with geospatial analysis and spatial database management, and related tools and languages (e.g., GDAL; PostgreSQL/PostGIS). Responsibilities Data Strategy and
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of phototrophs to environmental change Developing quantitative tools for the analysis of plant microbiome systems data, including but not limited to, machine learning, metabolic modeling (e.g. flux-balance models
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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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, including panel design and data analysis o Spatial biology methods o Experience studying adaptive immunity, e.g. in the context of vaccine development, cancer immunity, neuroimmunity, or autoimmunity
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platform for spatial multi-omic analysis of biological tissues. Our lab builds biological measurement infrastructure—engineering systems that standardize how information is extracted from complex biological
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the objectives more precise; working on the individual PhD study project with its focus on the methodological contributions as well as on empirical data processing for the case study analysis in collaboration with
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respect to the basics of the technology, instrument startup/shutdown and maintenance, data acquisition and transfer, and data analysis as needed. Educate core laboratory clients with respect to sample
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spatial transcriptomics. Candidates must hold (or be on track to receive) a PhD, MD, or MD/PhD degree. Application Requirements Document requirements Curriculum Vitae - Your most recently updated C.V