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%). This post will support analysis of multiomics data (e.g. single cell and single nuclear RNA-seq, spatial transcriptomics, proteomics etc.) generated by the Borne Uterine Mapping Project (BUMP, focussed
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, early modern and modern world history. We are an intellectual home for scholars of every region of the world, who use approaches which range from local micro-histories to large-scale quantitative analysis
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the Spatial Biology Facility, you will lead the development and optimisation of high-resolution spatial biology and multi-omics data analysis pipelines. Your primary focus (80% of your time) will be on leading
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imaging. The successful candidate will play a key role in recruiting and supporting pregnant participants, coordinating MRI scans, and inputting into data collection and analysis. The post is ideal for a
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genetics and genomics or a related field with a proven track record in the analysis of large biological datasets. They are expected to be able to work effectively as part of a team but also to direct
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research outputs Data science skills, especially data analysis and prediction modelling Proven ability to write code in Python Experience working in a research team Excellent writing and communication skills
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, the development and fine-tuning of vision foundation models, multiple instance learning, survival analysis, and interpretable model development. You will also lead efforts in building multimodal deep learning