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Field
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analysis in a setting with ample expertise and infrastructure. This is a rare opportunity to develop expertise in quantitative pathology in the burgeoning field of spatial cancer biology. Ours is a diverse
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laboratory experience, such as: DNA/RNA extraction, PCR, cloning, virus production, ELISA, etc. Computational biology laboratory experience, such as: bulk- singl cell- or spatial-transcriptomic data analysis
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Supervisor: Dr Guiping Wang Course start date: 1st October 2027 Project details For further information about the research group, please visit our website at https://www.cruk.cam.ac.uk/research
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circulating tumor DNA, with comprehensive tissue-based profiling methods such as gene expression analysis, DNA sequencing, single-cell sequencing, and spatial transcriptomics. These high-dimensional data
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of novel diabetes therapies Precision medicine for Type 1 and Type 2 diabetes Human pancreas imaging and spatial biology Digital pathology and computational tissue analysis Clinical decision support using
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Network ReDiLEEP (https://redileep.eu/ ). ReDiLEEP brings together leading universities, research institutes, and non-academic partners across Europe and beyond to advance response diversity research and
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Glioblastoma (GBM) is an aggressive brain tumour whose progression is strongly influenced by communication between tumour cells and the brain microenvironment. These interactions are spatially organised
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modalities, spatial scales, and diverse populations. Position Highlights Work with cutting-edge multimodal concurrent stimulation-recording datasets spanning iES, TMS, iEEG, single-unit, and fMRI. Study causal
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Good knowledge of aquatic ecology Experience with geographical information systems and spatial analysis Experience with sociological survey design Experience with ecological field studies About us Do you
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omics-based approaches. Interest in spatial biology, single-cell/spatial omics technologies and the integration of tissue-based, molecular and clinical data. Basic computational and data-analysis skills