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tumours and metastases with the goal to design combinatorial therapeutic approaches. The project will involve the use of genetically complex organoid-derived transplantation mouse models of pancreatic
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processes associated with CIN [1], leveraging single-cell DNA sequencing understand CIN heterogeneity [2], and development and implementation of machine learning and AI models to imaging data [3]. The student
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: Advanced molecular and protein analysis Mass spectrometry-based imaging Multi-omics technologies Preclinical cardiometabolic animal models They will also gain professional development in data stewardship
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mouse models and immunology expertise (CRUK-CI), access to relevant patient material (matched fresh-frozen PDAC and serum samples). We will utilize AstraZeneca expertise in spatial and circulatory
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microscopies, ultrafast photophysics, X-ray, THz, superresolution, modelling. Further details including funding information is available at: www.nanodtc.cam.ac.uk/apply/ For entry in October 2026, applications
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Immunoprecipitation Mass spectrometry of Endogenous complexes). We have identified about 50 proteins that can associate with Ascl1 or other NEPC transcription factors, some of which are enzymes that could in theory be
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computational modelling to be used to design and re-engineer flower architecture. The RA's main focus will be on computational modelling of gene regulatory networks for predicting the mechanisms leading
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on cell viability and DDR activation in established human cell models. The student will perform CRISPR screens to determine factors that affect resistance/sensitivity and follow these up with mechanistic
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chromatin profiling methods along with CRISPR/Cas9-meduated cell line engineering and various animal models. You will study the effects of the activation or depletion of chromatin-modifying enzymes using
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prostate cancer risk across diverse ethnic groups. This work aims to support more equitable risk stratification in cancer screening programmes. Using simulations based on multistate modelling framework