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on digital spatial profiling of human issues and applying analytical frameworks, The final salary and offer components are subject to additional approvals based on UC policy. Your placement within the salary
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Massachusetts Institute of Technology (MIT) | Cambridge, Massachusetts | United States | 19 days ago
/Administrative Internal Number: 25518 RESEARCH SCIENTIST 3, CHUNG LAB, Picower Institute for Learning and Memory, is a pivotal role responsible for generating spatial transcriptomic and proteomic optical imaging
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Massachusetts Institute of Technology (MIT) | Cambridge, Massachusetts | United States | 19 days ago
/Administrative Internal Number: 25519 RESEARCH SCIENTIST 1, CHUNG LAB, Picower Institute for Learning and Memory, is a pivotal role responsible for generating spatial transcriptomic and proteomic optical imaging
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experience working with GIS systems and spatial data, including Esri products Experience performing GIS data edits and maintenance, including working with CAD-based construction drawings The anticipated hiring
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and structures in biomedical image data. Additionally, the candidate will analyze spatial transcriptomic data to evaluate spatial patterns of genes in tissues. They will primarily work on projects
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: The Center for Spatial Information Science and Systems (CSISS) is an interdisciplinary research center affiliated with the College of Science at George Mason University. The mission of the Center is to conduct
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“Enhancing Machine Learning Approaches for Spatially Dependent Data in Fisheries and Environmental Research” (CMAT, University of Minho), reference 2024.15617.PEX, financed by national funds through
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the causal circuits driving the development and the functional specialisation of the largest macrophage population in the body: the liver-resident Kupffer cells. You will next develop Spatial CRISPR screens in
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Position Announcement Chair, Department of Geography & Spatial Sciences, College of Earth, Ocean and Environment, University of Delaware The Department of Geography & Spatial Sciences (GEOG) is
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(immunohistochemistry/fluorescence, in situ hybridization) and emerging spatial transcriptomic technologies coupled to a robust image capture and semi-automated image segmentation pipeline to enable the large-scale