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Field
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. Profieciency in histopathology work such as tissue sectioning, conducting 10X single-cell RNAseq (wet lab) and conducting spatial transcriptomics (wet lab or data analysis) is desirable. Application Process You
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production and visual sensitivity, a web-based LCOE calculator, and a multi-criteria decision analysis (MCDA) methodology for comparing candidate demonstrator sites. The project directly supports Action 3 and
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well as collaborative work on the high-resolution structure of the podocyte slit diaphragm. The Oxford Kidney Pathology (Bull) Group have an interest in structurally informed analysis of kidney spatial transcriptomics
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with the analysis of scSeq datasets from human peripheral blood mononuclear cells and varied disaggregated tissues (e.g. synovium, gut, skin) Excellent bioinformatics skills, including proficiency with
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the cognitive neuroscience of language, multilingualism and spatial cognition, including entorhinal cortex based spatial grids and cognitive maps. The ideal candidate holds a degree in Biomedical Engineering
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Do you have a strong mathematical background in geometry or numerical analysis? Are you inspired by applications to engineering, physics, or industrial problems? Do you thrive in a multi
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, viability and biological function. The work will require rigorous experimental design, appropriate controls and benchmarks, statistical analysis, traceable data and predefined acceptance criteria. The role
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, or computational analysis of clinically annotated cancer datasets. Experience with multi-omics data integration, including DNA sequencing, bulk and single-cell RNA sequencing, spatial transcriptomics, methylation
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, or equivalent) conferred by the start date. 2. Proficiency in R/Python. 3. Experience with spatial proteomic/transcriptomic data analysis. 4. Growth mindset and motivation to advance our understanding of breast
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, Spatial data analysis or GIS Whole-genome sequencing, phylogenetics, or phylodynamics Data management and reproducible analytical workflows Quantitative modeling and statistical inference. Applicants