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in the structured PhD programme at the Department of Mathematics & Statistics (https://www.reading.ac.uk/maths-and-stats/ ) About the project/work tasks: This position is part of: 19 PhD Fellowships
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months - expiration date 21st november 2025 at 1:00 pm - at the Department of Information Engineering Where to apply Website http://www.unipi.it Requirements Additional Information Eligibility criteria
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modelling framework to develop new understandings Full time, four-years fixed-term, based in Hobart About the opportunity This postdoctoral research position will develop and apply an optimal spatial
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Volcanic islands are exciting real-world climate and landscape laboratories. When geologically young (<10Ma) they provide a simplified and spatially limited setting for testing landscape evolution
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uses cutting-edge techniques including single-cell and spatial transcriptomics, proteomics, super-resolution microscopy, in vivo tracking, mouse models, and human patient tissues and iPS-derived cells
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and how alloimmunity is suppressed in patients receiving donor hematopoietic stem cells. In addition, the lab is using novel, spatial omics approaches to more comprehensively understand transplant
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proficiency in integrating spatial data into 3D models using sophisticated interpolation techniques. Additionally, the postdoctoral researcher will contribute to transforming mining liabilities into valuable
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 2 months ago
on new techniques, software, and equipment, as well as providing guidance to work study students working in the lab. They will perform routine and higher-level histopathology and spatial biology tasks
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 2 months ago
The Histology Specialist will become familiar with all aspects of working in the Pathology Services Core. They will perform routine and higher level histopathology and spatial biology tasks. Standard histology
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Your Job: Develop methods and workflows to construct robust co-regulation networks from large single-cell and spatial transcriptomics datasets Integrate ontologies and metadata (e.g., tissue, cell