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development and application of mass spectrometry-based spatial phosphoproteomics workflows for the analysis of formalin-fixed paraffin-embedded (FFPE) biopsy material. Specifically, you will establish
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interdisciplinary work in the areas of spatial biology, image analysis, single-cell biology and genomics. The research group is embedded in the Wallenberg Center for Molecular and Translational Medicine (WCMTM) and
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Mapping of Actors, Linkages, and Interdependencies (Field work) - Spatial Analysis and Scenario Modeling of Governance Innovations - Analyzing Vulnerabilities, Asymmetries, and Externalities
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Full-Time Fixed-Term for 36 months This PhD aims to develop novel robotic monitoring and data processing methods to document changes in dynamic seafloor environments over large spatial scales
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or spatiotemporal analysis, geospatial data, integration of observations across spatial or temporal scales, or methods for estimating pollutant emissions. Experience designing environmental monitoring or sampling
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Genomics and Therapeutics Division (PI Dr. Simona Migliozzi, PhD) The GarMiglio Lab (https://garmigliolab.com/) led by Dr. Luciano Garofano (Assistant Professor) and Dr. Simona Migliozzi (Assistant Professor
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Memorial Sloan Kettering Cancer Center | New York City, New York | United States | about 9 hours ago
Role Overview: We are seeking a highly motivated computational biology postdoctoral fellow to lead translational studies in single cell and spatial biology of gastric cancer immunology and evolution
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, chromatin-accessibility, and spatial data where appropriate. Developing or adapting computational approaches for large-scale data integration, predictive modelling, gene-regulatory analysis, and cell-fate
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This PhD aims to develop novel robotic monitoring and data processing methods to document changes in dynamic seafloor environments over large spatial scales. Motivation: Understanding how
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This PhD aims to develop novel robotic monitoring and data processing methods to document changes in dynamic seafloor environments over large spatial scales. Motivation: Understanding how