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Field
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Cancer Research UK strategic programme investigating how colorectal cancer responds to therapy through the integration of spatial biology, computational analysis and clinical research. Working across
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major Cancer Research UK strategic programme investigating how colorectal cancer responds to therapy through the integration of spatial biology, computational analysis and clinical research. Working
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the analysis of proteomic data, as well as experience in spatial proteomics (laser capture), single cell proteomics and MALDI Imaging. Previous research experience in the genetics of human disease is desirable
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proteomics, advanced image analysis, and computational approaches to investigate molecular and cellular heterogeneity and to integrate spatial molecular information with histopathological and clinical data. We
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. The successful candidate will provide lab-based functional validation of scRNA-seq and spatial transcriptomic findings, translating these into clinically relevant therapeutic targets. The role offers
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: Experience with georeferencing and geoprocessing tools applied to urban studies, including the organization, processing, analysis, and spatial representation of data. Strong academic track record, with
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cells, and their spatial organization within the tumor microenvironment. We use spatial transcriptomics and spatial proteomics, advanced image analysis, and computational approaches to investigate
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, R, MATLAB) for data processing and analysis. - Experience in statistical processing of spatial and temporal data. 4) Instrumentation and metrology: - Knowledge of sensors and measurement instruments
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develop next-generation computational approaches to understand cellular and tissue biology from single-cell, spatial, imaging, and multimodal molecular data. You will develop models that capture cellular
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, genomics, or computational analysis of high-dimensional datasets. Experience with one or more of the following: Flow cytometry Single-cell sequencing Spatial transcriptomics Multiplex imaging Bioinformatics