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Field
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learning informed by the results of biophysical simulations in the prediction and analysis of cell organisation in tumoroids. Cells are active and can both manipulate and be manipulated by their environment
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together to answer some of the most important questions about the causes, prevention and treatment of disease. We are seeking to appoint a Postdoctoral Researcher in Biomedical Image Analysis to join the
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: 1089, bioRxiv (2025)) by carrying out protein biochemical, cell biological, and live cell fluorescence imaging experiments. Associated structural analysis of the proteins by cryo-electron microscopy will
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analysis techniques, including space syntax, isovist measures, and visual complexity assessments. The successful candidate will work closely with researchers at Cambridge and ETH Zurich to quantify spatial
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responsible for adapting existing mathematical and statistical methods for analysis of high-dimensional imaging data, and analysing quantitative imaging data from a variety of sources, including Spatial
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will also develop skills in mathematical modelling and spatial analysis via independent study and training courses. It is essential that you hold a PhD/DPhil (or close to completion) in mathematics
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, including Spatial Transcriptomics and Multiplex Immunofluorescence platforms, for validation and calibration of mathematical models. You will also develop skills in mathematical modelling and spatial analysis
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Institute, MI), Professor Simon Leedham (NDM), Dr Joshua Moore (MI) and Dr Eoghan Mulholland (NDM). You will be responsible for adapting existing mathematical and statistical methods for analysis of high
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About Us We are seeking experts in medical image deep learning to join our team and help develop novel computationally efficient segmentation algorithms. We welcome application from individual with experience in: Deep learning Medical imaging computing (preferably neuroimaging) Computationally...
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About us: We are seeking experts in medical image deep learning to join our team and help develop novel computationally efficient segmentation algorithms. We welcome application from individual with experience in: Deep learning Medical imaging computing (preferably neuroimaging) Computationally...